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Sample records for monocular images based

  1. Grey and white matter changes in children with monocular amblyopia: voxel-based morphometry and diffusion tensor imaging study.

    Science.gov (United States)

    Li, Qian; Jiang, Qinying; Guo, Mingxia; Li, Qingji; Cai, Chunquan; Yin, Xiaohui

    2013-04-01

    To investigate the potential morphological alterations of grey and white matter in monocular amblyopic children using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). A total of 20 monocular amblyopic children and 20 age-matched controls were recruited. Whole-brain MRI scans were performed after a series of ophthalmologic exams. The imaging data were processed and two-sample t-tests were employed to identify group differences in grey matter volume (GMV), white matter volume (WMV) and fractional anisotropy (FA). After image screening, there were 12 amblyopic participants and 15 normal controls qualified for the VBM analyses. For DTI analysis, 14 amblyopes and 14 controls were included. Compared to the normal controls, reduced GMVs were observed in the left inferior occipital gyrus, the bilateral parahippocampal gyrus and the left supramarginal/postcentral gyrus in the monocular amblyopic group, with the lingual gyrus presenting augmented GMV. Meanwhile, WMVs reduced in the left calcarine, the bilateral inferior frontal and the right precuneus areas, and growth in the WMVs was seen in the right cuneus, right middle occipital and left orbital frontal areas. Diminished FA values in optic radiation and increased FA in the left middle occipital area and right precuneus were detected in amblyopic patients. In monocular amblyopia, cortices related to spatial vision underwent volume loss, which provided neuroanatomical evidence of stereoscopic defects. Additionally, white matter development was also hindered due to visual defects in amblyopes. Growth in the GMVs, WMVs and FA in the occipital lobe and precuneus may reflect a compensation effect by the unaffected eye in monocular amblyopia.

  2. Robot Navigation Control Based on Monocular Images: An Image Processing Algorithm for Obstacle Avoidance Decisions

    Directory of Open Access Journals (Sweden)

    William Benn

    2012-01-01

    Full Text Available This paper covers the use of monocular vision to control autonomous navigation for a robot in a dynamically changing environment. The solution focused on using colour segmentation against a selected floor plane to distinctly separate obstacles from traversable space: this is then supplemented with canny edge detection to separate similarly coloured boundaries to the floor plane. The resulting binary map (where white identifies an obstacle-free area and black identifies an obstacle could then be processed by fuzzy logic or neural networks to control the robot’s next movements. Findings show that the algorithm performed strongly on solid coloured carpets, wooden, and concrete floors but had difficulty in separating colours in multicoloured floor types such as patterned carpets.

  3. Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity

    Directory of Open Access Journals (Sweden)

    Taekjun Oh

    2015-07-01

    Full Text Available Localization is an essential issue for robot navigation, allowing the robot to perform tasks autonomously. However, in environments with laser scan ambiguity, such as long corridors, the conventional SLAM (simultaneous localization and mapping algorithms exploiting a laser scanner may not estimate the robot pose robustly. To resolve this problem, we propose a novel localization approach based on a hybrid method incorporating a 2D laser scanner and a monocular camera in the framework of a graph structure-based SLAM. 3D coordinates of image feature points are acquired through the hybrid method, with the assumption that the wall is normal to the ground and vertically flat. However, this assumption can be relieved, because the subsequent feature matching process rejects the outliers on an inclined or non-flat wall. Through graph optimization with constraints generated by the hybrid method, the final robot pose is estimated. To verify the effectiveness of the proposed method, real experiments were conducted in an indoor environment with a long corridor. The experimental results were compared with those of the conventional GMappingapproach. The results demonstrate that it is possible to localize the robot in environments with laser scan ambiguity in real time, and the performance of the proposed method is superior to that of the conventional approach.

  4. Smartphone Image Acquisition During Postmortem Monocular Indirect Ophthalmoscopy.

    Science.gov (United States)

    Lantz, Patrick E; Schoppe, Candace H; Thibault, Kirk L; Porter, William T

    2016-01-01

    The medical usefulness of smartphones continues to evolve as third-party applications exploit and expand on the smartphones' interface and capabilities. This technical report describes smartphone still-image capture techniques and video-sequence recording capabilities during postmortem monocular indirect ophthalmoscopy. Using these devices and techniques, practitioners can create photographic documentation of fundal findings, clinically and at autopsy, without the expense of a retinal camera. Smartphone image acquisition of fundal abnormalities can promote ophthalmological telemedicine--especially in regions or countries with limited resources--and facilitate prompt, accurate, and unbiased documentation of retinal hemorrhages in infants and young children. © 2015 American Academy of Forensic Sciences.

  5. Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis

    Directory of Open Access Journals (Sweden)

    Chen Shih-Wei

    2011-11-01

    Full Text Available Abstract Background The computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD. In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA. Method Twelve PD patients and twelve healthy adults with no neurological history or motor disorders within the past six months were recruited and separated according to their "Non-PD", "Drug-On", and "Drug-Off" states. The participants were asked to wear light-colored clothing and perform three walking trials through a corridor decorated with a navy curtain at their natural pace. The participants' gait performance during the steady-state walking period was captured by a digital camera for gait analysis. The collected walking image frames were then transformed into binary silhouettes for noise reduction and compression. Using the developed KPCA-based method, the features within the binary silhouettes can be extracted to quantitatively determine the gait cycle time, stride length, walking velocity, and cadence. Results and Discussion The KPCA-based method uses a feature-extraction approach, which was verified to be more effective than traditional image area and principal component analysis (PCA approaches in classifying "Non-PD" controls and "Drug-Off/On" PD patients. Encouragingly, this method has a high accuracy rate, 80.51%, for recognizing different gaits. Quantitative gait parameters are obtained, and the power spectrums of the patients' gaits are analyzed. We show that that the slow and irregular actions of PD patients during walking tend to transfer some of the power from the main lobe frequency to a lower frequency band. Our results indicate the feasibility of using gait performance to evaluate the motor function of patients with PD. Conclusion This KPCA-based method requires only a digital camera and a decorated corridor setup

  6. Three-dimensional location of target fish by monocular infrared imaging sensor based on a L-z correlation model

    Science.gov (United States)

    Lin, Kai; Zhou, Chao; Xu, Daming; Guo, Qiang; Yang, Xinting; Sun, Chuanheng

    2018-01-01

    Monitoring of fish behavior has drawn extensive attention in pharmacological research, water environmental assessment, bio-inspired robot design and aquaculture. Given that an infrared sensor is low cost, no illumination limitation and electromagnetic interference, interest in its use in behavior monitoring has grown considerably, especially in 3D trajectory monitoring to quantify fish behavior on the basis of near infrared absorption of water. However, precise position of vertical dimension (z) remains a challenge, which greatly impacts on infrared tracking system accuracy. Hence, an intensity (L) and coordinate (z) correlation model was proposed to overcome the limitation. In the modelling process, two cameras (top view and side view) were employed synchronously to identify the 3D coordinate of each fish (x-y and z, respectively), and the major challenges were the distortion caused by the perspective effect and the refraction at water boundaries. Therefore, a coordinate correction formulation was designed firstly for the calibration. Then the L-z correlation model was established based on Lambert's absorption law and statistical data analysis, and the model was estimated through monitoring 3D trajectories of four fishes during the day and night. Finally, variations of individuals and limits of the depth detection of the model were discussed. Compared with previous studies, the favorable prediction performance of the model is achieved for 3D trajectory monitoring, which could provide some inspirations for fish behavior monitoring, especially for nocturnal behavior study.

  7. High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

    Science.gov (United States)

    Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

    2017-09-01

    Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

  8. Monocular Visual Odometry Based on Trifocal Tensor Constraint

    Science.gov (United States)

    Chen, Y. J.; Yang, G. L.; Jiang, Y. X.; Liu, X. Y.

    2018-02-01

    For the problem of real-time precise localization in the urban street, a monocular visual odometry based on Extend Kalman fusion of optical-flow tracking and trifocal tensor constraint is proposed. To diminish the influence of moving object, such as pedestrian, we estimate the motion of the camera by extracting the features on the ground, which improves the robustness of the system. The observation equation based on trifocal tensor constraint is derived, which can form the Kalman filter alone with the state transition equation. An Extend Kalman filter is employed to cope with the nonlinear system. Experimental results demonstrate that, compares with Yu’s 2-step EKF method, the algorithm is more accurate which meets the needs of real-time accurate localization in cities.

  9. A low cost PSD-based monocular motion capture system

    Science.gov (United States)

    Ryu, Young Kee; Oh, Choonsuk

    2007-10-01

    This paper describes a monocular PSD-based motion capture sensor to employ with commercial video game systems such as Microsoft's XBOX and Sony's Playstation II. The system is compact, low-cost, and only requires a one-time calibration at the factory. The system includes a PSD(Position Sensitive Detector) and active infrared (IR) LED markers that are placed on the object to be tracked. The PSD sensor is placed in the focal plane of a wide-angle lens. The micro-controller calculates the 3D position of the markers using only the measured intensity and the 2D position on the PSD. A series of experiments were performed to evaluate the performance of our prototype system. From the experimental results we see that the proposed system has the advantages of the compact size, the low cost, the easy installation, and the high frame rates to be suitable for high speed motion tracking in games.

  10. The monocular visual imaging technology model applied in the airport surface surveillance

    Science.gov (United States)

    Qin, Zhe; Wang, Jian; Huang, Chao

    2013-08-01

    At present, the civil aviation airports use the surface surveillance radar monitoring and positioning systems to monitor the aircrafts, vehicles and the other moving objects. Surface surveillance radars can cover most of the airport scenes, but because of the terminals, covered bridges and other buildings geometry, surface surveillance radar systems inevitably have some small segment blind spots. This paper presents a monocular vision imaging technology model for airport surface surveillance, achieving the perception of scenes of moving objects such as aircrafts, vehicles and personnel location. This new model provides an important complement for airport surface surveillance, which is different from the traditional surface surveillance radar techniques. Such technique not only provides clear objects activities screen for the ATC, but also provides image recognition and positioning of moving targets in this area. Thereby it can improve the work efficiency of the airport operations and avoid the conflict between the aircrafts and vehicles. This paper first introduces the monocular visual imaging technology model applied in the airport surface surveillance and then the monocular vision measurement accuracy analysis of the model. The monocular visual imaging technology model is simple, low cost, and highly efficient. It is an advanced monitoring technique which can make up blind spot area of the surface surveillance radar monitoring and positioning systems.

  11. A flexible approach to light pen calibration for a monocular-vision-based coordinate measuring system

    International Nuclear Information System (INIS)

    Fu, Shuai; Zhang, Liyan; Ye, Nan; Liu, Shenglan; Zhang, WeiZhong

    2014-01-01

    A monocular-vision-based coordinate measuring system (MVB-CMS) obtains the 3D coordinates of the probe tip center of a light pen by analyzing the monocular image of the target points on the light pen. The light pen calibration, including the target point calibration and the probe tip center calibration, is critical to guarantee the accuracy of the MVB-CMS. The currently used method resorts to special equipment to calibrate the feature points on the light pen in a separate offsite procedure and uses the system camera to calibrate the probe tip center onsite. Instead, a complete onsite light pen calibration method is proposed in this paper. It needs only several auxiliary target points with the same visual features of the light pen targets and two or more cone holes with known distance(s). The target point calibration and the probe tip center calibration are jointly implemented by simply taking two groups of images of the light pen with the camera of the system. The proposed method requires no extra equipment other than the system camera for the calibration, so it is easier to implement and flexible for use. It has been incorporated in a large field-of-view MVB-CMS, which uses active luminous infrared LEDs as the target points. Experimental results demonstrate the accuracy and effectiveness of the proposed method. (paper)

  12. Optic disc boundary segmentation from diffeomorphic demons registration of monocular fundus image sequences versus 3D visualization of stereo fundus image pairs for automated early stage glaucoma assessment

    Science.gov (United States)

    Gatti, Vijay; Hill, Jason; Mitra, Sunanda; Nutter, Brian

    2014-03-01

    Despite the current availability in resource-rich regions of advanced technologies in scanning and 3-D imaging in current ophthalmology practice, world-wide screening tests for early detection and progression of glaucoma still consist of a variety of simple tools, including fundus image-based parameters such as CDR (cup to disc diameter ratio) and CAR (cup to disc area ratio), especially in resource -poor regions. Reliable automated computation of the relevant parameters from fundus image sequences requires robust non-rigid registration and segmentation techniques. Recent research work demonstrated that proper non-rigid registration of multi-view monocular fundus image sequences could result in acceptable segmentation of cup boundaries for automated computation of CAR and CDR. This research work introduces a composite diffeomorphic demons registration algorithm for segmentation of cup boundaries from a sequence of monocular images and compares the resulting CAR and CDR values with those computed manually by experts and from 3-D visualization of stereo pairs. Our preliminary results show that the automated computation of CDR and CAR from composite diffeomorphic segmentation of monocular image sequences yield values comparable with those from the other two techniques and thus may provide global healthcare with a cost-effective yet accurate tool for management of glaucoma in its early stage.

  13. Joint optic disc and cup boundary extraction from monocular fundus images.

    Science.gov (United States)

    Chakravarty, Arunava; Sivaswamy, Jayanthi

    2017-08-01

    Accurate segmentation of optic disc and cup from monocular color fundus images plays a significant role in the screening and diagnosis of glaucoma. Though optic cup is characterized by the drop in depth from the disc boundary, most existing methods segment the two structures separately and rely only on color and vessel kink based cues due to the lack of explicit depth information in color fundus images. We propose a novel boundary-based Conditional Random Field formulation that extracts both the optic disc and cup boundaries in a single optimization step. In addition to the color gradients, the proposed method explicitly models the depth which is estimated from the fundus image itself using a coupled, sparse dictionary trained on a set of image-depth map (derived from Optical Coherence Tomography) pairs. The estimated depth achieved a correlation coefficient of 0.80 with respect to the ground truth. The proposed segmentation method outperformed several state-of-the-art methods on five public datasets. The average dice coefficient was in the range of 0.87-0.97 for disc segmentation across three datasets and 0.83 for cup segmentation on the DRISHTI-GS1 test set. The method achieved a good glaucoma classification performance with an average AUC of 0.85 for five fold cross-validation on RIM-ONE v2. We propose a method to jointly segment the optic disc and cup boundaries by modeling the drop in depth between the two structures. Since our method requires a single fundus image per eye during testing it can be employed in the large-scale screening of glaucoma where expensive 3D imaging is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Detection and Tracking Strategies for Autonomous Aerial Refuelling Tasks Based on Monocular Vision

    Directory of Open Access Journals (Sweden)

    Yingjie Yin

    2014-07-01

    Full Text Available Detection and tracking strategies based on monocular vision are proposed for autonomous aerial refuelling tasks. The drogue attached to the fuel tanker aircraft has two important features. The grey values of the drogue's inner part are different from the external umbrella ribs, as shown in the image. The shape of the drogue's inner dark part is nearly circular. According to crucial prior knowledge, the rough and fine positioning algorithms are designed to detect the drogue. Particle filter based on the drogue's shape is proposed to track the drogue. A strategy to switch between detection and tracking is proposed to improve the robustness of the algorithms. The inner dark part of the drogue is segmented precisely in the detecting and tracking process and the segmented circular part can be used to measure its spatial position. The experimental results show that the proposed method has good performance in real-time and satisfied robustness and positioning accuracy.

  15. Monocular Vision-Based Robot Localization and Target Tracking

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    Bing-Fei Wu

    2011-01-01

    Full Text Available This paper presents a vision-based technology for localizing targets in 3D environment. It is achieved by the combination of different types of sensors including optical wheel encoders, an electrical compass, and visual observations with a single camera. Based on the robot motion model and image sequences, extended Kalman filter is applied to estimate target locations and the robot pose simultaneously. The proposed localization system is applicable in practice because it is not necessary to have the initializing setting regarding starting the system from artificial landmarks of known size. The technique is especially suitable for navigation and target tracing for an indoor robot and has a high potential extension to surveillance and monitoring for Unmanned Aerial Vehicles with aerial odometry sensors. The experimental results present “cm” level accuracy of the localization of the targets in indoor environment under a high-speed robot movement.

  16. Real-Time Vehicle Speed Estimation Based on License Plate Tracking in Monocular Video Sequences

    Directory of Open Access Journals (Sweden)

    Aleksej MAKAROV

    2016-02-01

    Full Text Available A method of estimating the vehicle speed from images obtained by a fixed over-the-road monocular camera is presented. The method is based on detecting and tracking vehicle license plates. The contrast between the license plate and its surroundings is enhanced using infrared light emitting diodes and infrared camera filters. A range of the license plate height values is assumed a priori. The camera vertical angle of view is measured prior to installation. The camera tilt is continuously measured by a micro-electromechanical sensor. The distance of the license plate from the camera is theoretically derived in terms of its pixel coordinates. Inaccuracies due to the frame rate drift, to the tilt and the angle of view measurement errors, to edge pixel detection and to a coarse assumption of the vehicle license plate height are analyzed and theoretically formulated. The resulting system is computationally efficient, inexpensive and easy to install and maintain along with the existing ALPR cameras.

  17. Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments.

    Science.gov (United States)

    Trujillo, Juan-Carlos; Munguia, Rodrigo; Guerra, Edmundo; Grau, Antoni

    2018-04-26

    This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.

  18. A Monocular Vision Measurement System of Three-Degree-of-Freedom Air-Bearing Test-Bed Based on FCCSP

    Science.gov (United States)

    Gao, Zhanyu; Gu, Yingying; Lv, Yaoyu; Xu, Zhenbang; Wu, Qingwen

    2018-06-01

    A monocular vision-based pose measurement system is provided for real-time measurement of a three-degree-of-freedom (3-DOF) air-bearing test-bed. Firstly, a circular plane cooperative target is designed. An image of a target fixed on the test-bed is then acquired. Blob analysis-based image processing is used to detect the object circles on the target. A fast algorithm (FCCSP) based on pixel statistics is proposed to extract the centers of object circles. Finally, pose measurements can be obtained when combined with the centers and the coordinate transformation relation. Experiments show that the proposed method is fast, accurate, and robust enough to satisfy the requirement of the pose measurement.

  19. Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

    Directory of Open Access Journals (Sweden)

    Tao Liu

    2017-02-01

    Full Text Available Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

  20. 3D display system using monocular multiview displays

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    Sakamoto, Kunio; Saruta, Kazuki; Takeda, Kazutoki

    2002-05-01

    A 3D head mounted display (HMD) system is useful for constructing a virtual space. The authors have researched the virtual-reality systems connected with computer networks for real-time remote control and developed a low-priced real-time 3D display for building these systems. We developed a 3D HMD system using monocular multi-view displays. The 3D displaying technique of this monocular multi-view display is based on the concept of the super multi-view proposed by Kajiki at TAO (Telecommunications Advancement Organization of Japan) in 1996. Our 3D HMD has two monocular multi-view displays (used as a visual display unit) in order to display a picture to the left eye and the right eye. The left and right images are a pair of stereoscopic images for the left and right eyes, then stereoscopic 3D images are observed.

  1. Optimization of dynamic envelope measurement system for high speed train based on monocular vision

    Science.gov (United States)

    Wu, Bin; Liu, Changjie; Fu, Luhua; Wang, Zhong

    2018-01-01

    The definition of dynamic envelope curve is the maximum limit outline caused by various adverse effects during the running process of the train. It is an important base of making railway boundaries. At present, the measurement work of dynamic envelope curve of high-speed vehicle is mainly achieved by the way of binocular vision. There are some problems of the present measuring system like poor portability, complicated process and high cost. A new measurement system based on the monocular vision measurement theory and the analysis on the test environment is designed and the measurement system parameters, the calibration of camera with wide field of view, the calibration of the laser plane are designed and optimized in this paper. The accuracy has been verified to be up to 2mm by repeated tests and experimental data analysis. The feasibility and the adaptability of the measurement system is validated. There are some advantages of the system like lower cost, a simpler measurement and data processing process, more reliable data. And the system needs no matching algorithm.

  2. SLAM-based dense surface reconstruction in monocular Minimally Invasive Surgery and its application to Augmented Reality.

    Science.gov (United States)

    Chen, Long; Tang, Wen; John, Nigel W; Wan, Tao Ruan; Zhang, Jian Jun

    2018-05-01

    based on a robust 3D calibration. We demonstrate the clinical relevance of our proposed system through two examples: (a) measurement of the surface; (b) depth cues in monocular endoscopy. The performance and accuracy evaluations of the proposed framework consist of two steps. First, we have created a computer-generated endoscopy simulation video to quantify the accuracy of the camera tracking by comparing the results of the video camera tracking with the recorded ground-truth camera trajectories. The accuracy of the surface reconstruction is assessed by evaluating the Root Mean Square Distance (RMSD) of surface vertices of the reconstructed mesh with that of the ground truth 3D models. An error of 1.24 mm for the camera trajectories has been obtained and the RMSD for surface reconstruction is 2.54 mm, which compare favourably with previous approaches. Second, in vivo laparoscopic videos are used to examine the quality of accurate AR based annotation and measurement, and the creation of depth cues. These results show the potential promise of our geometry-aware AR technology to be used in MIS surgical scenes. The results show that the new framework is robust and accurate in dealing with challenging situations such as the rapid endoscopy camera movements in monocular MIS scenes. Both camera tracking and surface reconstruction based on a sparse point cloud are effective and operated in real-time. This demonstrates the potential of our algorithm for accurate AR localization and depth augmentation with geometric cues and correct surface measurements in MIS with monocular endoscopes. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Monocular Vision SLAM for Indoor Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Koray Çelik

    2013-01-01

    Full Text Available This paper presents a novel indoor navigation and ranging strategy via monocular camera. By exploiting the architectural orthogonality of the indoor environments, we introduce a new method to estimate range and vehicle states from a monocular camera for vision-based SLAM. The navigation strategy assumes an indoor or indoor-like manmade environment whose layout is previously unknown, GPS-denied, representable via energy based feature points, and straight architectural lines. We experimentally validate the proposed algorithms on a fully self-contained microaerial vehicle (MAV with sophisticated on-board image processing and SLAM capabilities. Building and enabling such a small aerial vehicle to fly in tight corridors is a significant technological challenge, especially in the absence of GPS signals and with limited sensing options. Experimental results show that the system is only limited by the capabilities of the camera and environmental entropy.

  4. Manifolds for pose tracking from monocular video

    Science.gov (United States)

    Basu, Saurav; Poulin, Joshua; Acton, Scott T.

    2015-03-01

    We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

  5. Estimated Prevalence of Monocular Blindness and Monocular ...

    African Journals Online (AJOL)

    with MB/MSVI; among the 109 (51%) children with MB/MSVI that had a known etiology, trauma. Table 1: Major anatomical site of monocular blindness and monocular severe visual impairment in children. Anatomical cause. Total (%). Corneal scar. 89 (42). Whole globe. 43 (20). Lens. 42 (19). Amblyopia. 16 (8). Retina. 9 (4).

  6. A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

    Science.gov (United States)

    Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

    2015-08-31

    Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.

  7. A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

    Directory of Open Access Journals (Sweden)

    Hyungjin Kim

    2015-08-01

    Full Text Available Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments

  8. Automatic Human Facial Expression Recognition Based on Integrated Classifier From Monocular Video with Uncalibrated Camera

    Directory of Open Access Journals (Sweden)

    Yu Tao

    2017-01-01

    Full Text Available An automatic recognition framework for human facial expressions from a monocular video with an uncalibrated camera is proposed. The expression characteristics are first acquired from a kind of deformable template, similar to a facial muscle distribution. After associated regularization, the time sequences from the trait changes in space-time under complete expressional production are then arranged line by line in a matrix. Next, the matrix dimensionality is reduced by a method of manifold learning of neighborhood-preserving embedding. Finally, the refined matrix containing the expression trait information is recognized by a classifier that integrates the hidden conditional random field (HCRF and support vector machine (SVM. In an experiment using the Cohn–Kanade database, the proposed method showed a comparatively higher recognition rate than the individual HCRF or SVM methods in direct recognition from two-dimensional human face traits. Moreover, the proposed method was shown to be more robust than the typical Kotsia method because the former contains more structural characteristics of the data to be classified in space-time

  9. Gain-scheduling control of a monocular vision-based human-following robot

    CSIR Research Space (South Africa)

    Burke, Michael G

    2011-08-01

    Full Text Available , R. and Zisserman, A. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press, 2nd edition. Hutchinson, S., Hager, G., and Corke, P. (1996). A tutorial on visual servo control. IEEE Trans. on Robotics and Automation, 12... environment, in a passive manner, at relatively high speeds and low cost. The control of mobile robots using vision in the feed- back loop falls into the well-studied field of visual servo control. Two primary approaches are used: image-based visual...

  10. Fiducial-based monocular 3D displacement measurement of breakwater armour unit models.

    CSIR Research Space (South Africa)

    Vieira, R

    2008-11-01

    Full Text Available This paper presents a fiducial-based approach to monitoring the movement of breakwater armour units in a model hall environment. Target symbols with known dimensions are attached to the physical models, allowing the recovery of three...

  11. Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

    Science.gov (United States)

    Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

    2011-01-01

    Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

  12. 6DoF object pose measurement by a monocular manifold-based pattern recognition technique

    International Nuclear Information System (INIS)

    Kouskouridas, Rigas; Charalampous, Konstantinos; Gasteratos, Antonios

    2012-01-01

    In this paper, a novel solution to the compound problem of object recognition and 3D pose estimation is presented. An accurate measurement of the geometrical configuration of a recognized target, relative to a known coordinate system, is of fundamental importance and constitutes a prerequisite for several applications such as robot grasping or obstacle avoidance. The proposed method lays its foundations on the following assumptions: (a) the same object captured under varying viewpoints and perspectives represents data that could be projected onto a well-established and highly distinguishable subspace; (b) totally different objects observed under the same viewpoints and perspectives share identical 3D pose that can be sufficiently modeled to produce a generalized model. Toward this end, we propose an advanced architecture that allows both recognizing patterns and providing efficient solution for 6DoF pose estimation. We employ a manifold modeling architecture that is grounded on a part-based representation of an object, which in turn, is accomplished via an unsupervised clustering of the extracted visual cues. The main contributions of the proposed framework are: (a) the proposed part-based architecture requires minimum supervision, compared to other contemporary solutions, whilst extracting new features encapsulating both appearance and geometrical attributes of the objects; (b) contrary to related projects that extract high-dimensional data, thus, increasing the complexity of the system, the proposed manifold modeling approach makes use of low dimensionality input vectors; (c) the formulation of a novel input–output space mapping that outperforms the existing dimensionality reduction schemes. Experimental results justify our theoretical claims and demonstrate the superiority of our method comparing to other related contemporary projects. (paper)

  13. Visual Suppression of Monocularly Presented Symbology Against a Fused Background in a Simulation and Training Environment

    National Research Council Canada - National Science Library

    Winterbottom, Marc D; Patterson, Robert; Pierce, Byron J; Taylor, Amanda

    2006-01-01

    .... This may create interocular differences in image characteristics that could disrupt binocular vision by provoking visual suppression, thus reducing visibility of the background scene, monocular symbology...

  14. Monocular Elevation Deficiency - Double Elevator Palsy

    Science.gov (United States)

    ... Español Condiciones Chinese Conditions Monocular Elevation Deficiency/ Double Elevator Palsy En Español Read in Chinese What is monocular elevation deficiency (Double Elevator Palsy)? Monocular Elevation Deficiency, also known by the ...

  15. Line-based monocular graph SLAM algorithm%基于图优化的单目线特征SLAM算法

    Institute of Scientific and Technical Information of China (English)

    董蕊芳; 柳长安; 杨国田; 程瑞营

    2017-01-01

    A new line based 6-DOF monocular algorithm for using graph simultaneous localization and mapping(SLAM) algoritm was proposed.First,the straight line were applied as a feature instead of points,due to a map consisting of a sparse set of 3D points is unable to describe the structure of the surrounding world.Secondly,most of previous line-based SLAM algorithms were focused on filtering-based solutions suffering from the inconsistent when applied to the inherently non-linear SLAM problem,in contrast,the graph-based solution was used to improve the accuracy of the localization and the consistency of mapping.Thirdly,a special line representation was exploited for combining the Plücker coordinates with the Cayley representation.The Plücker coordinates were used for the 3D line projection function,and the Cayley representation helps to update the line parameters during the non-linear optimization process.Finally,the simulation experiment shows that the proposed algorithm outperforms odometry and EKF-based SLAM in terms of the pose estimation,while the sum of the squared errors (SSE) and root-mean-square error (RMSE) of proposed method are 2.5% and 10.5% of odometry,and 22.4% and 33% of EKF-based SLAM.The reprojection error is only 45.5 pixels.The real image experiment shows that the proposed algorithm obtains only 958 cm2 and 3.941 3 cm the SSE and RMSE of pose estimation.Therefore,it can be concluded that the proposed algorithm is effective and accuracy.%提出了基于图优化的单目线特征同时定位和地图构建(SLAM)的方法.首先,针对主流视觉SLAM算法因采用点作为特征而导致构建的点云地图稀疏、难以准确表达环境结构信息等缺点,采用直线作为特征来构建地图.然后,根据现有线特征的SLAM算法都是基于滤波器的SLAM框架、存在线性化及更新效率的问题,采用基于图优化的SLAM解决方案以提高定位精度及地图构建的一致性和准确性.将线特征的Plücker坐

  16. A Highest Order Hypothesis Compatibility Test for Monocular SLAM

    OpenAIRE

    Edmundo Guerra; Rodrigo Munguia; Yolanda Bolea; Antoni Grau

    2013-01-01

    Simultaneous Location and Mapping (SLAM) is a key problem to solve in order to build truly autonomous mobile robots. SLAM with a unique camera, or monocular SLAM, is probably one of the most complex SLAM variants, based entirely on a bearing-only sensor working over six DOF. The monocular SLAM method developed in this work is based on the Delayed Inverse-Depth (DI-D) Feature Initialization, with the contribution of a new data association batch validation technique, the Highest Order Hyp...

  17. Monocular channels have a functional role in endogenous orienting.

    Science.gov (United States)

    Saban, William; Sekely, Liora; Klein, Raymond M; Gabay, Shai

    2018-03-01

    The literature has long emphasized the role of higher cortical structures in endogenous orienting. Based on evolutionary explanation and previous data, we explored the possibility that lower monocular channels may also have a functional role in endogenous orienting of attention. Sensitive behavioral manipulation was used to probe the contribution of monocularly segregated regions in a simple cue - target detection task. A central spatially informative cue, and its ensuing target, were presented to the same or different eyes at varying cue-target intervals. Results indicated that the onset of endogenous orienting was apparent earlier when the cue and target were presented to the same eye. The data provides converging evidence for the notion that endogenous facilitation is modulated by monocular portions of the visual stream. This, in turn, suggests that higher cortical mechanisms are not exclusively responsible for endogenous orienting, and that a dynamic interaction between higher and lower neural levels, might be involved. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Stereo using monocular cues within the tensor voting framework.

    Science.gov (United States)

    Mordohai, Philippos; Medioni, Gérard

    2006-06-01

    We address the fundamental problem of matching in two static images. The remaining challenges are related to occlusion and lack of texture. Our approach addresses these difficulties within a perceptual organization framework, considering both binocular and monocular cues. Initially, matching candidates for all pixels are generated by a combination of matching techniques. The matching candidates are then embedded in disparity space, where perceptual organization takes place in 3D neighborhoods and, thus, does not suffer from problems associated with scanline or image neighborhoods. The assumption is that correct matches produce salient, coherent surfaces, while wrong ones do not. Matching candidates that are consistent with the surfaces are kept and grouped into smooth layers. Thus, we achieve surface segmentation based on geometric and not photometric properties. Surface overextensions, which are due to occlusion, can be corrected by removing matches whose projections are not consistent in color with their neighbors of the same surface in both images. Finally, the projections of the refined surfaces on both images are used to obtain disparity hypotheses for unmatched pixels. The final disparities are selected after a second tensor voting stage, during which information is propagated from more reliable pixels to less reliable ones. We present results on widely used benchmark stereo pairs.

  19. Monocular SLAM for autonomous robots with enhanced features initialization.

    Science.gov (United States)

    Guerra, Edmundo; Munguia, Rodrigo; Grau, Antoni

    2014-04-02

    This work presents a variant approach to the monocular SLAM problem focused in exploiting the advantages of a human-robot interaction (HRI) framework. Based upon the delayed inverse-depth feature initialization SLAM (DI-D SLAM), a known monocular technique, several but crucial modifications are introduced taking advantage of data from a secondary monocular sensor, assuming that this second camera is worn by a human. The human explores an unknown environment with the robot, and when their fields of view coincide, the cameras are considered a pseudo-calibrated stereo rig to produce estimations for depth through parallax. These depth estimations are used to solve a related problem with DI-D monocular SLAM, namely, the requirement of a metric scale initialization through known artificial landmarks. The same process is used to improve the performance of the technique when introducing new landmarks into the map. The convenience of the approach taken to the stereo estimation, based on SURF features matching, is discussed. Experimental validation is provided through results from real data with results showing the improvements in terms of more features correctly initialized, with reduced uncertainty, thus reducing scale and orientation drift. Additional discussion in terms of how a real-time implementation could take advantage of this approach is provided.

  20. Monocular and binocular visual impairment in the UK Biobank study: prevalence, associations and diagnoses.

    Science.gov (United States)

    McKibbin, Martin; Farragher, Tracey M; Shickle, Darren

    2018-01-01

    To determine the prevalence of, associations with and diagnoses leading to mild visual impairment or worse (logMAR >0.3) in middle-aged adults in the UK Biobank study. Prevalence estimates for monocular and binocular visual impairment were determined for the UK Biobank participants with fundus photographs and spectral domain optical coherence tomography images. Associations with socioeconomic, biometric, lifestyle and medical variables were investigated for cases with visual impairment and matched controls, using multinomial logistic regression models. Self-reported eye history and image grading results were used to identify the primary diagnoses leading to visual impairment for a sample of 25% of cases. For the 65 033 UK Biobank participants, aged 40-69 years and with fundus images, 6682 (10.3%) and 1677 (2.6%) had mild visual impairment or worse in one or both eyes, respectively. Increasing deprivation, age and ethnicity were independently associated with both monocular and binocular visual impairment. No primary diagnosis for the recorded level of visual impairment could be identified for 49.8% of eyes. The most common identifiable diagnoses leading to visual impairment were cataract, amblyopia, uncorrected refractive error and vitreoretinal interface abnormalities. The prevalence of visual impairment in the UK Biobank study cohort is lower than for population-based studies from other industrialised countries. Monocular and binocular visual impairment are associated with increasing deprivation, age and ethnicity. The UK Biobank dataset does not allow confident identification of the causes of visual impairment, and the results may not be applicable to the wider UK population.

  1. Monocular and binocular visual impairment in the UK Biobank study: prevalence, associations and diagnoses

    Science.gov (United States)

    Farragher, Tracey M; Shickle, Darren

    2018-01-01

    Objective To determine the prevalence of, associations with and diagnoses leading to mild visual impairment or worse (logMAR >0.3) in middle-aged adults in the UK Biobank study. Methods and analysis Prevalence estimates for monocular and binocular visual impairment were determined for the UK Biobank participants with fundus photographs and spectral domain optical coherence tomography images. Associations with socioeconomic, biometric, lifestyle and medical variables were investigated for cases with visual impairment and matched controls, using multinomial logistic regression models. Self-reported eye history and image grading results were used to identify the primary diagnoses leading to visual impairment for a sample of 25% of cases. Results For the 65 033 UK Biobank participants, aged 40–69 years and with fundus images, 6682 (10.3%) and 1677 (2.6%) had mild visual impairment or worse in one or both eyes, respectively. Increasing deprivation, age and ethnicity were independently associated with both monocular and binocular visual impairment. No primary diagnosis for the recorded level of visual impairment could be identified for 49.8% of eyes. The most common identifiable diagnoses leading to visual impairment were cataract, amblyopia, uncorrected refractive error and vitreoretinal interface abnormalities. Conclusions The prevalence of visual impairment in the UK Biobank study cohort is lower than for population-based studies from other industrialised countries. Monocular and binocular visual impairment are associated with increasing deprivation, age and ethnicity. The UK Biobank dataset does not allow confident identification of the causes of visual impairment, and the results may not be applicable to the wider UK population. PMID:29657974

  2. Monocular Perceptual Deprivation from Interocular Suppression Temporarily Imbalances Ocular Dominance.

    Science.gov (United States)

    Kim, Hyun-Woong; Kim, Chai-Youn; Blake, Randolph

    2017-03-20

    Early visual experience sculpts neural mechanisms that regulate the balance of influence exerted by the two eyes on cortical mechanisms underlying binocular vision [1, 2], and experience's impact on this neural balancing act continues into adulthood [3-5]. One recently described, compelling example of adult neural plasticity is the effect of patching one eye for a relatively short period of time: contrary to intuition, monocular visual deprivation actually improves the deprived eye's competitive advantage during a subsequent period of binocular rivalry [6-8], the robust form of visual competition prompted by dissimilar stimulation of the two eyes [9, 10]. Neural concomitants of this improvement in monocular dominance are reflected in measurements of brain responsiveness following eye patching [11, 12]. Here we report that patching an eye is unnecessary for producing this paradoxical deprivation effect: interocular suppression of an ordinarily visible stimulus being viewed by one eye is sufficient to produce shifts in subsequent predominance of that eye to an extent comparable to that produced by patching the eye. Moreover, this imbalance in eye dominance can also be induced by prior, extended viewing of two monocular images differing only in contrast. Regardless of how shifts in eye dominance are induced, the effect decays once the two eyes view stimuli equal in strength. These novel findings implicate the operation of interocular neural gain control that dynamically adjusts the relative balance of activity between the two eyes [13, 14]. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO

    Directory of Open Access Journals (Sweden)

    M. S. Temiz

    2012-07-01

    Full Text Available In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.

  4. A Highest Order Hypothesis Compatibility Test for Monocular SLAM

    Directory of Open Access Journals (Sweden)

    Edmundo Guerra

    2013-08-01

    Full Text Available Simultaneous Location and Mapping (SLAM is a key problem to solve in order to build truly autonomous mobile robots. SLAM with a unique camera, or monocular SLAM, is probably one of the most complex SLAM variants, based entirely on a bearing-only sensor working over six DOF. The monocular SLAM method developed in this work is based on the Delayed Inverse-Depth (DI-D Feature Initialization, with the contribution of a new data association batch validation technique, the Highest Order Hypothesis Compatibility Test, HOHCT. The Delayed Inverse-Depth technique is used to initialize new features in the system and defines a single hypothesis for the initial depth of features with the use of a stochastic technique of triangulation. The introduced HOHCT method is based on the evaluation of statistically compatible hypotheses and a search algorithm designed to exploit the strengths of the Delayed Inverse-Depth technique to achieve good performance results. This work presents the HOHCT with a detailed formulation of the monocular DI-D SLAM problem. The performance of the proposed HOHCT is validated with experimental results, in both indoor and outdoor environments, while its costs are compared with other popular approaches.

  5. Does monocular visual space contain planes?

    NARCIS (Netherlands)

    Koenderink, J.J.; Albertazzi, L.; Doorn, A.J. van; Ee, R. van; Grind, W.A. van de; Kappers, A.M.L.; Lappin, J.S.; Norman, J.F.; Oomes, A.H.J.; Pas, S.F. te; Phillips, F.; Pont, S.C.; Richards, W.A.; Todd, J.T.; Verstraten, F.A.J.; Vries, S.C. de

    2010-01-01

    The issue of the existence of planes—understood as the carriers of a nexus of straight lines—in the monocular visual space of a stationary human observer has never been addressed. The most recent empirical data apply to binocular visual space and date from the 1960s (Foley, 1964). This appears to be

  6. Does monocular visual space contain planes?

    NARCIS (Netherlands)

    Koenderink, Jan J.; Albertazzi, Liliana; van Doorn, Andrea J.; van Ee, Raymond; van de Grind, Wim A.; Kappers, Astrid M L; Lappin, Joe S.; Farley Norman, J.; (Stijn) Oomes, A. H J; te Pas, Susan P.; Phillips, Flip; Pont, Sylvia C.; Richards, Whitman A.; Todd, James T.; Verstraten, Frans A J; de Vries, Sjoerd

    The issue of the existence of planes-understood as the carriers of a nexus of straight lines-in the monocular visual space of a stationary human observer has never been addressed. The most recent empirical data apply to binocular visual space and date from the 1960s (Foley, 1964). This appears to be

  7. Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle.

    Science.gov (United States)

    Ito, Seigo; Hiratsuka, Shigeyoshi; Ohta, Mitsuhiko; Matsubara, Hiroyuki; Ogawa, Masaru

    2018-01-10

    We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy.

  8. Recovery of neurofilament following early monocular deprivation

    Directory of Open Access Journals (Sweden)

    Timothy P O'Leary

    2012-04-01

    Full Text Available A brief period of monocular deprivation in early postnatal life can alter the structure of neurons within deprived-eye-receiving layers of the dorsal lateral geniculate nucleus. The modification of structure is accompanied by a marked reduction in labeling for neurofilament, a protein that composes the stable cytoskeleton and that supports neuron structure. This study examined the extent of neurofilament recovery in monocularly deprived cats that either had their deprived eye opened (binocular recovery, or had the deprivation reversed to the fellow eye (reverse occlusion. The degree to which recovery was dependent on visually-driven activity was examined by placing monocularly deprived animals in complete darkness (dark rearing. The loss of neurofilament and the reduction of soma size caused by monocular deprivation were both ameliorated equally following either binocular recovery or reverse occlusion for 8 days. Though monocularly deprived animals placed in complete darkness showed recovery of soma size, there was a generalized loss of neurofilament labeling that extended to originally non-deprived layers. Overall, these results indicate that recovery of soma size is achieved by removal of the competitive disadvantage of the deprived eye, and occurred even in the absence of visually-driven activity. Recovery of neurofilament occurred when the competitive disadvantage of the deprived eye was removed, but unlike the recovery of soma size, was dependent upon visually-driven activity. The role of neurofilament in providing stable neural structure raises the intriguing possibility that dark rearing, which reduced overall neurofilament levels, could be used to reset the deprived visual system so as to make it more ameliorable with treatment by experiential manipulations.

  9. Preliminary Results for a Monocular Marker-Free Gait Measurement System

    Directory of Open Access Journals (Sweden)

    Jane Courtney

    2006-01-01

    Full Text Available This paper presents results from a novel monocular marker-free gait measurement system. The system was designed for physical and occupational therapists to monitor the progress of patients through therapy. It is based on a novel human motion capturemethod derived from model-based tracking. Testing is performed on two monocular, sagittal-view, sample gait videos – one with both the environment and the subject’s appearance and movement restricted and one in a natural environment with unrestrictedclothing and motion. Results of the modelling, tracking and analysis stages are presented along with standard gait graphs and parameters.

  10. Monocular deprivation of Fourier phase information boosts the deprived eye's dominance during interocular competition but not interocular phase combination.

    Science.gov (United States)

    Bai, Jianying; Dong, Xue; He, Sheng; Bao, Min

    2017-06-03

    Ocular dominance has been extensively studied, often with the goal to understand neuroplasticity, which is a key characteristic within the critical period. Recent work on monocular deprivation, however, demonstrates residual neuroplasticity in the adult visual cortex. After deprivation of patterned inputs by monocular patching, the patched eye becomes more dominant. Since patching blocks both the Fourier amplitude and phase information of the input image, it remains unclear whether deprivation of the Fourier phase information alone is able to reshape eye dominance. Here, for the first time, we show that removing of the phase regularity without changing the amplitude spectra of the input image induced a shift of eye dominance toward the deprived eye, but only if the eye dominance was measured with a binocular rivalry task rather than an interocular phase combination task. These different results indicate that the two measurements are supported by different mechanisms. Phase integration requires the fusion of monocular images. The fused percept highly relies on the weights of the phase-sensitive monocular neurons that respond to the two monocular images. However, binocular rivalry reflects the result of direct interocular competition that strongly weights the contour information transmitted along each monocular pathway. Monocular phase deprivation may not change the weights in the integration (fusion) mechanism much, but alters the balance in the rivalry (competition) mechanism. Our work suggests that ocular dominance plasticity may occur at different stages of visual processing, and that homeostatic compensation also occurs for the lack of phase regularity in natural scenes. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  11. Monocular depth effects on perceptual fading.

    Science.gov (United States)

    Hsu, Li-Chuan; Kramer, Peter; Yeh, Su-Ling

    2010-08-06

    After prolonged viewing, a static target among moving non-targets is perceived to repeatedly disappear and reappear. An uncrossed stereoscopic disparity of the target facilitates this Motion-Induced Blindness (MIB). Here we test whether monocular depth cues can affect MIB too, and whether they can also affect perceptual fading in static displays. Experiment 1 reveals an effect of interposition: more MIB when the target appears partially covered by, than when it appears to cover, its surroundings. Experiment 2 shows that the effect is indeed due to interposition and not to the target's contours. Experiment 3 induces depth with the watercolor illusion and replicates Experiment 1. Experiments 4 and 5 replicate Experiments 1 and 3 without the use of motion. Since almost any stimulus contains a monocular depth cue, we conclude that perceived depth affects perceptual fading in almost any stimulus, whether dynamic or static. Copyright 2010 Elsevier Ltd. All rights reserved.

  12. On so-called paradoxical monocular stereoscopy.

    Science.gov (United States)

    Koenderink, J J; van Doorn, A J; Kappers, A M

    1994-01-01

    Human observers are apparently well able to judge properties of 'three-dimensional objects' on the basis of flat pictures such as photographs of physical objects. They obtain this 'pictorial relief' without much conscious effort and with little interference from the (flat) picture surface. Methods for 'magnifying' pictorial relief from single pictures include viewing instructions as well as a variety of monocular and binocular 'viewboxes'. Such devices are reputed to yield highly increased pictorial depth, though no methodologies for the objective verification of such claims exist. A binocular viewbox has been reconstructed and pictorial relief under monocular, 'synoptic', and natural binocular viewing is described. The results corroborate and go beyond early introspective reports and turn out to pose intriguing problems for modern research.

  13. Distributed Monocular SLAM for Indoor Map Building

    OpenAIRE

    Ruwan Egodagamage; Mihran Tuceryan

    2017-01-01

    Utilization and generation of indoor maps are critical elements in accurate indoor tracking. Simultaneous Localization and Mapping (SLAM) is one of the main techniques for such map generation. In SLAM an agent generates a map of an unknown environment while estimating its location in it. Ubiquitous cameras lead to monocular visual SLAM, where a camera is the only sensing device for the SLAM process. In modern applications, multiple mobile agents may be involved in the generation of such maps,...

  14. The Enright phenomenon. Stereoscopic distortion of perceived driving speed induced by monocular pupil dilation.

    Science.gov (United States)

    Carkeet, Andrew; Wood, Joanne M; McNeill, Kylie M; McNeill, Hamish J; James, Joanna A; Holder, Leigh S

    The Enright phenomenon describes the distortion in speed perception experienced by an observer looking sideways from a moving vehicle when viewing with interocular differences in retinal image brightness, usually induced by neutral density filters. We investigated whether the Enright phenomenon could be induced with monocular pupil dilation using tropicamide. We tested 17 visually normal young adults on a closed road driving circuit. Participants were asked to travel at Goal Speeds of 40km/h and 60km/h while looking sideways from the vehicle with: (i) both eyes with undilated pupils; (ii) both eyes with dilated pupils; (iii) with the leading eye only dilated; and (iv) the trailing eye only dilated. For each condition we recorded actual driving speed. With the pupil of the leading eye dilated participants drove significantly faster (by an average of 3.8km/h) than with both eyes dilated (p=0.02); with the trailing eye dilated participants drove significantly slower (by an average of 3.2km/h) than with both eyes dilated (p<0.001). The speed, with the leading eye dilated, was faster by an average of 7km/h than with the trailing eye dilated (p<0.001). There was no significant difference between driving speeds when viewing with both eyes either dilated or undilated (p=0.322). Our results are the first to show a measurable change in driving behaviour following monocular pupil dilation and support predictions based on the Enright phenomenon. Copyright © 2016 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.

  15. Dictionary Based Image Segmentation

    DEFF Research Database (Denmark)

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets...

  16. A Novel Metric Online Monocular SLAM Approach for Indoor Applications

    Directory of Open Access Journals (Sweden)

    Yongfei Li

    2016-01-01

    Full Text Available Monocular SLAM has attracted more attention recently due to its flexibility and being economic. In this paper, a novel metric online direct monocular SLAM approach is proposed, which can obtain the metric reconstruction of the scene. In the proposed approach, a chessboard is utilized to provide initial depth map and scale correction information during the SLAM process. The involved chessboard provides the absolute scale of scene, and it is seen as a bridge between the camera visual coordinate and the world coordinate. The scene is reconstructed as a series of key frames with their poses and correlative semidense depth maps, using a highly accurate pose estimation achieved by direct grid point-based alignment. The estimated pose is coupled with depth map estimation calculated by filtering over a large number of pixelwise small-baseline stereo comparisons. In addition, this paper formulates the scale-drift model among key frames and the calibration chessboard is used to correct the accumulated pose error. At the end of this paper, several indoor experiments are conducted. The results suggest that the proposed approach is able to achieve higher reconstruction accuracy when compared with the traditional LSD-SLAM approach. And the approach can also run in real time on a commonly used computer.

  17. Transient monocular blindness and the risk of vascular complications according to subtype : a prospective cohort study

    NARCIS (Netherlands)

    Volkers, Eline J; Donders, Richard C J M; Koudstaal, Peter J; van Gijn, Jan; Algra, Ale; Jaap Kappelle, L

    Patients with transient monocular blindness (TMB) can present with many different symptoms, and diagnosis is usually based on the history alone. In this study, we assessed the risk of vascular complications according to different characteristics of TMB. We prospectively studied 341 consecutive

  18. Transient monocular blindness and the risk of vascular complications according to subtype: a prospective cohort study

    NARCIS (Netherlands)

    Volkers, E.J. (Eline J.); R. Donders (Rogier); P.J. Koudstaal (Peter Jan); van Gijn, J. (Jan); A. Algra (Ale); L. Jaap Kappelle

    2016-01-01

    textabstractPatients with transient monocular blindness (TMB) can present with many different symptoms, and diagnosis is usually based on the history alone. In this study, we assessed the risk of vascular complications according to different characteristics of TMB. We prospectively studied 341

  19. Depth of Monocular Elements in a Binocular Scene: The Conditions for da Vinci Stereopsis

    Science.gov (United States)

    Cook, Michael; Gillam, Barbara

    2004-01-01

    Quantitative depth based on binocular resolution of visibility constraints is demonstrated in a novel stereogram representing an object, visible to 1 eye only, and seen through an aperture or camouflaged against a background. The monocular region in the display is attached to the binocular region, so that the stereogram represents an object which…

  20. Object-based connectedness facilitates matching

    NARCIS (Netherlands)

    Koning, A.R.; Lier, R.J. van

    2003-01-01

    In two matching tasks, participants had to match two images of object pairs. Image-based (113) connectedness refers to connectedness between the objects in an image. Object-based (OB) connectedness refers to connectedness between the interpreted objects. In Experiment 1, a monocular depth cue

  1. Localisation accuracy of semi-dense monocular SLAM

    Science.gov (United States)

    Schreve, Kristiaan; du Plessies, Pieter G.; Rätsch, Matthias

    2017-06-01

    Understanding the factors that influence the accuracy of visual SLAM algorithms is very important for the future development of these algorithms. So far very few studies have done this. In this paper, a simulation model is presented and used to investigate the effect of the number of scene points tracked, the effect of the baseline length in triangulation and the influence of image point location uncertainty. It is shown that the latter is very critical, while the other all play important roles. Experiments with a well known semi-dense visual SLAM approach are also presented, when used in a monocular visual odometry mode. The experiments shows that not including sensor bias and scale factor uncertainty is very detrimental to the accuracy of the simulation results.

  2. IMAGE DESCRIPTIONS FOR SKETCH BASED IMAGE RETRIEVAL

    OpenAIRE

    SAAVEDRA RONDO, JOSE MANUEL; SAAVEDRA RONDO, JOSE MANUEL

    2008-01-01

    Due to the massive use of Internet together with the proliferation of media devices, content based image retrieval has become an active discipline in computer science. A common content based image retrieval approach requires that the user gives a regular image (e.g, a photo) as a query. However, having a regular image as query may be a serious problem. Indeed, people commonly use an image retrieval system because they do not count on the desired image. An easy alternative way t...

  3. Distributed Monocular SLAM for Indoor Map Building

    Directory of Open Access Journals (Sweden)

    Ruwan Egodagamage

    2017-01-01

    Full Text Available Utilization and generation of indoor maps are critical elements in accurate indoor tracking. Simultaneous Localization and Mapping (SLAM is one of the main techniques for such map generation. In SLAM an agent generates a map of an unknown environment while estimating its location in it. Ubiquitous cameras lead to monocular visual SLAM, where a camera is the only sensing device for the SLAM process. In modern applications, multiple mobile agents may be involved in the generation of such maps, thus requiring a distributed computational framework. Each agent can generate its own local map, which can then be combined into a map covering a larger area. By doing so, they can cover a given environment faster than a single agent. Furthermore, they can interact with each other in the same environment, making this framework more practical, especially for collaborative applications such as augmented reality. One of the main challenges of distributed SLAM is identifying overlapping maps, especially when relative starting positions of agents are unknown. In this paper, we are proposing a system having multiple monocular agents, with unknown relative starting positions, which generates a semidense global map of the environment.

  4. Nanoplatform-based molecular imaging

    National Research Council Canada - National Science Library

    Chen, Xiaoyuan

    2011-01-01

    "Nanoplathform-Based Molecular Imaging provides rationale for using nanoparticle-based probes for molecular imaging, then discusses general strategies for this underutilized, yet promising, technology...

  5. Effect of monocular deprivation on rabbit neural retinal cell densities

    Directory of Open Access Journals (Sweden)

    Philip Maseghe Mwachaka

    2015-01-01

    Conclusion: In this rabbit model, monocular deprivation resulted in activity-dependent changes in cell densities of the neural retina in favour of the non-deprived eye along with reduced cell densities in the deprived eye.

  6. Effect of Monocular Deprivation on Rabbit Neural Retinal Cell Densities

    OpenAIRE

    Mwachaka, Philip Maseghe; Saidi, Hassan; Odula, Paul Ochieng; Mandela, Pamela Idenya

    2015-01-01

    Purpose: To describe the effect of monocular deprivation on densities of neural retinal cells in rabbits. Methods: Thirty rabbits, comprised of 18 subject and 12 control animals, were included and monocular deprivation was achieved through unilateral lid suturing in all subject animals. The rabbits were observed for three weeks. At the end of each week, 6 experimental and 3 control animals were euthanized, their retinas was harvested and processed for light microscopy. Photomicrographs of ...

  7. ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras

    OpenAIRE

    Mur-Artal, Raul; Tardos, Juan D.

    2016-01-01

    We present ORB-SLAM2 a complete SLAM system for monocular, stereo and RGB-D cameras, including map reuse, loop closing and relocalization capabilities. The system works in real-time on standard CPUs in a wide variety of environments from small hand-held indoors sequences, to drones flying in industrial environments and cars driving around a city. Our back-end based on bundle adjustment with monocular and stereo observations allows for accurate trajectory estimation with metric scale. Our syst...

  8. Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning

    Science.gov (United States)

    van Hecke, Kevin; de Croon, Guido C. H. E.; Hennes, Daniel; Setterfield, Timothy P.; Saenz-Otero, Alvar; Izzo, Dario

    2017-11-01

    Although machine learning holds an enormous promise for autonomous space robots, it is currently not employed because of the inherent uncertain outcome of learning processes. In this article we investigate a learning mechanism, Self-Supervised Learning (SSL), which is very reliable and hence an important candidate for real-world deployment even on safety-critical systems such as space robots. To demonstrate this reliability, we introduce a novel SSL setup that allows a stereo vision equipped robot to cope with the failure of one of its cameras. The setup learns to estimate average depth using a monocular image, by using the stereo vision depths from the past as trusted ground truth. We present preliminary results from an experiment on the International Space Station (ISS) performed with the MIT/NASA SPHERES VERTIGO satellite. The presented experiments were performed on October 8th, 2015 on board the ISS. The main goals were (1) data gathering, and (2) navigation based on stereo vision. First the astronaut Kimiya Yui moved the satellite around the Japanese Experiment Module to gather stereo vision data for learning. Subsequently, the satellite freely explored the space in the module based on its (trusted) stereo vision system and a pre-programmed exploration behavior, while simultaneously performing the self-supervised learning of monocular depth estimation on board. The two main goals were successfully achieved, representing the first online learning robotic experiments in space. These results lay the groundwork for a follow-up experiment in which the satellite will use the learned single-camera depth estimation for autonomous exploration in the ISS, and are an advancement towards future space robots that continuously improve their navigation capabilities over time, even in harsh and completely unknown space environments.

  9. Distance Estimation by Fusing Radar and Monocular Camera with Kalman Filter

    OpenAIRE

    Feng, Yuxiang; Pickering, Simon; Chappell, Edward; Iravani, Pejman; Brace, Christian

    2017-01-01

    The major contribution of this paper is to propose a low-cost accurate distance estimation approach. It can potentially be used in driver modelling, accident avoidance and autonomous driving. Based on MATLAB and Python, sensory data from a Continental radar and a monocular dashcam were fused using a Kalman filter. Both sensors were mounted on a Volkswagen Sharan, performing repeated driving on a same route. The established system consists of three components, radar data processing, camera dat...

  10. Binocular contrast discrimination needs monocular multiplicative noise

    Science.gov (United States)

    Ding, Jian; Levi, Dennis M.

    2016-01-01

    The effects of signal and noise on contrast discrimination are difficult to separate because of a singularity in the signal-detection-theory model of two-alternative forced-choice contrast discrimination (Katkov, Tsodyks, & Sagi, 2006). In this article, we show that it is possible to eliminate the singularity by combining that model with a binocular combination model to fit monocular, dichoptic, and binocular contrast discrimination. We performed three experiments using identical stimuli to measure the perceived phase, perceived contrast, and contrast discrimination of a cyclopean sine wave. In the absence of a fixation point, we found a binocular advantage in contrast discrimination both at low contrasts (discrimination mechanisms: a nonlinear contrast transducer and multiplicative noise (MN). A binocular combination model (the DSKL model; Ding, Klein, & Levi, 2013b) was first fitted to both the perceived-phase and the perceived-contrast data sets, then combined with either the nonlinear contrast transducer or the MN mechanism to fit the contrast-discrimination data. We found that the best model combined the DSKL model with early MN. Model simulations showed that, after going through interocular suppression, the uncorrelated noise in the two eyes became anticorrelated, resulting in less binocular noise and therefore a binocular advantage in the discrimination task. Combining a nonlinear contrast transducer or MN with a binocular combination model (DSKL) provides a powerful method for evaluating the two putative contrast-discrimination mechanisms. PMID:26982370

  11. Relating binocular and monocular vision in strabismic and anisometropic amblyopia.

    Science.gov (United States)

    Agrawal, Ritwick; Conner, Ian P; Odom, J V; Schwartz, Terry L; Mendola, Janine D

    2006-06-01

    To examine deficits in monocular and binocular vision in adults with amblyopia and to test the following 2 hypotheses: (1) Regardless of clinical subtype, the degree of impairment in binocular integration predicts the pattern of monocular acuity deficits. (2) Subjects who lack binocular integration exhibit the most severe interocular suppression. Seven subjects with anisometropia, 6 subjects with strabismus, and 7 control subjects were tested. Monocular tests included Snellen acuity, grating acuity, Vernier acuity, and contrast sensitivity. Binocular tests included Titmus stereo test, binocular motion integration, and dichoptic contrast masking. As expected, both groups showed deficits in monocular acuity, with subjects with strabismus showing greater deficits in Vernier acuity. Both amblyopic groups were then characterized according to the degree of residual stereoacuity and binocular motion integration ability, and 67% of subjects with strabismus compared with 29% of subjects with anisometropia were classified as having "nonbinocular" vision according to our criterion. For this nonbinocular group, Vernier acuity is most impaired. In addition, the nonbinocular group showed the most dichoptic contrast masking of the amblyopic eye and the least dichoptic contrast masking of the fellow eye. The degree of residual binocularity and interocular suppression predicts monocular acuity and may be a significant etiological mechanism of vision loss.

  12. Separating monocular and binocular neural mechanisms mediating chromatic contextual interactions.

    Science.gov (United States)

    D'Antona, Anthony D; Christiansen, Jens H; Shevell, Steven K

    2014-04-17

    When seen in isolation, a light that varies in chromaticity over time is perceived to oscillate in color. Perception of that same time-varying light may be altered by a surrounding light that is also temporally varying in chromaticity. The neural mechanisms that mediate these contextual interactions are the focus of this article. Observers viewed a central test stimulus that varied in chromaticity over time within a larger surround that also varied in chromaticity at the same temporal frequency. Center and surround were presented either to the same eye (monocular condition) or to opposite eyes (dichoptic condition) at the same frequency (3.125, 6.25, or 9.375 Hz). Relative phase between center and surround modulation was varied. In both the monocular and dichoptic conditions, the perceived modulation depth of the central light depended on the relative phase of the surround. A simple model implementing a linear combination of center and surround modulation fit the measurements well. At the lowest temporal frequency (3.125 Hz), the surround's influence was virtually identical for monocular and dichoptic conditions, suggesting that at this frequency, the surround's influence is mediated primarily by a binocular neural mechanism. At higher frequencies, the surround's influence was greater for the monocular condition than for the dichoptic condition, and this difference increased with temporal frequency. Our findings show that two separate neural mechanisms mediate chromatic contextual interactions: one binocular and dominant at lower temporal frequencies and the other monocular and dominant at higher frequencies (6-10 Hz).

  13. SLAMM: Visual monocular SLAM with continuous mapping using multiple maps.

    Directory of Open Access Journals (Sweden)

    Hayyan Afeef Daoud

    Full Text Available This paper presents the concept of Simultaneous Localization and Multi-Mapping (SLAMM. It is a system that ensures continuous mapping and information preservation despite failures in tracking due to corrupted frames or sensor's malfunction; making it suitable for real-world applications. It works with single or multiple robots. In a single robot scenario the algorithm generates a new map at the time of tracking failure, and later it merges maps at the event of loop closure. Similarly, maps generated from multiple robots are merged without prior knowledge of their relative poses; which makes this algorithm flexible. The system works in real time at frame-rate speed. The proposed approach was tested on the KITTI and TUM RGB-D public datasets and it showed superior results compared to the state-of-the-arts in calibrated visual monocular keyframe-based SLAM. The mean tracking time is around 22 milliseconds. The initialization is twice as fast as it is in ORB-SLAM, and the retrieved map can reach up to 90 percent more in terms of information preservation depending on tracking loss and loop closure events. For the benefit of the community, the source code along with a framework to be run with Bebop drone are made available at https://github.com/hdaoud/ORBSLAMM.

  14. Computer-based endoscopic image-processing technology for endourology and laparoscopic surgery

    International Nuclear Information System (INIS)

    Igarashi, Tatsuo; Suzuki, Hiroyoshi; Naya, Yukio

    2009-01-01

    Endourology and laparoscopic surgery are evolving in accordance with developments in instrumentation and progress in surgical technique. Recent advances in computer and image-processing technology have enabled novel images to be created from conventional endoscopic and laparoscopic video images. Such technology harbors the potential to advance endourology and laparoscopic surgery by adding new value and function to the endoscope. The panoramic and three-dimensional images created by computer processing are two outstanding features that can address the shortcomings of conventional endoscopy and laparoscopy, such as narrow field of view, lack of depth cue, and discontinuous information. The wide panoramic images show an anatomical map' of the abdominal cavity and hollow organs with high brightness and resolution, as the images are collected from video images taken in a close-up manner. To assist in laparoscopic surgery, especially in suturing, a three-dimensional movie can be obtained by enhancing movement parallax using a conventional monocular laparoscope. In tubular organs such as the prostatic urethra, reconstruction of three-dimensional structure can be achieved, implying the possibility of a liquid dynamic model for assessing local urethral resistance in urination. Computer-based processing of endoscopic images will establish new tools for endourology and laparoscopic surgery in the near future. (author)

  15. Aerial vehicles collision avoidance using monocular vision

    Science.gov (United States)

    Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

    2016-10-01

    In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

  16. Short-Term Monocular Deprivation Enhances Physiological Pupillary Oscillations

    Directory of Open Access Journals (Sweden)

    Paola Binda

    2017-01-01

    Full Text Available Short-term monocular deprivation alters visual perception in adult humans, increasing the dominance of the deprived eye, for example, as measured with binocular rivalry. This form of plasticity may depend upon the inhibition/excitation balance in the visual cortex. Recent work suggests that cortical excitability is reliably tracked by dilations and constrictions of the pupils of the eyes. Here, we ask whether monocular deprivation produces a systematic change of pupil behavior, as measured at rest, that is independent of the change of visual perception. During periods of minimal sensory stimulation (in the dark and task requirements (minimizing body and gaze movements, slow pupil oscillations, “hippus,” spontaneously appear. We find that hippus amplitude increases after monocular deprivation, with larger hippus changes in participants showing larger ocular dominance changes (measured by binocular rivalry. This tight correlation suggests that a single latent variable explains both the change of ocular dominance and hippus. We speculate that the neurotransmitter norepinephrine may be implicated in this phenomenon, given its important role in both plasticity and pupil control. On the practical side, our results indicate that measuring the pupil hippus (a simple and short procedure provides a sensitive index of the change of ocular dominance induced by short-term monocular deprivation, hence a proxy for plasticity.

  17. A novel visual-inertial monocular SLAM

    Science.gov (United States)

    Yue, Xiaofeng; Zhang, Wenjuan; Xu, Li; Liu, JiangGuo

    2018-02-01

    With the development of sensors and computer vision research community, cameras, which are accurate, compact, wellunderstood and most importantly cheap and ubiquitous today, have gradually been at the center of robot location. Simultaneous localization and mapping (SLAM) using visual features, which is a system getting motion information from image acquisition equipment and rebuild the structure in unknown environment. We provide an analysis of bioinspired flights in insects, employing a novel technique based on SLAM. Then combining visual and inertial measurements to get high accuracy and robustness. we present a novel tightly-coupled Visual-Inertial Simultaneous Localization and Mapping system which get a new attempt to address two challenges which are the initialization problem and the calibration problem. experimental results and analysis show the proposed approach has a more accurate quantitative simulation of insect navigation, which can reach the positioning accuracy of centimeter level.

  18. A Case of Complete Recovery of Fluctuating Monocular Blindness Following Endovascular Treatment in Internal Carotid Artery Dissection.

    Science.gov (United States)

    Kim, Ki-Tae; Baik, Seung Guk; Park, Kyung-Pil; Park, Min-Gyu

    2015-09-01

    Monocular blindness may appear as the first symptom of internal carotid artery dissection (ICAD). However, there have been no reports that monocular visual loss repeatedly occurs and disappears in response to postural change in ICAD. A 33-year-old woman presented with transient monocular blindness (TMB) following acute-onset headache. TMB repeatedly occurred in response to postural change. Two days later, she experienced transient dysarthria and right hemiparesis in upright position. Pupil size and light reflex were normal, but a relative afferent pupillary defect was positive in the left eye. Diffusion-weighted imaging showed no acute lesion, but perfusion-weighted imaging showed perfusion delay in the left ICA territory. Digital subtraction angiography demonstrated a false lumen and an intraluminal filling defect in proximal segment of the left ICA. Carotid stenting was performed urgently. After carotid stenting, left relative afferent pupillary defect disappeared and TMB was not provoked anymore by upright posture. At discharge, left visual acuity was completely normalized. Because fluctuating visual symptoms in the ICAD may be associated with hemodynamically unstable status, assessment of the perfusion status should be done quickly. Carotid stenting may be helpful to improve the fluctuating visual symptoms and hemodynamically unstable status in selected patient with the ICAD. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  19. Evidence-based cancer imaging

    Energy Technology Data Exchange (ETDEWEB)

    Shinagare, Atul B.; Khorasani, Ramin [Dept. of Radiology, Brigham and Women' s Hospital, Boston (Korea, Republic of)

    2017-01-15

    With the advances in the field of oncology, imaging is increasingly used in the follow-up of cancer patients, leading to concerns about over-utilization. Therefore, it has become imperative to make imaging more evidence-based, efficient, cost-effective and equitable. This review explores the strategies and tools to make diagnostic imaging more evidence-based, mainly in the context of follow-up of cancer patients.

  20. Disseminated neurocysticercosis presenting as isolated acute monocular painless vision loss

    Directory of Open Access Journals (Sweden)

    Gaurav M Kasundra

    2014-01-01

    Full Text Available Neurocysticercosis, the most common parasitic infection of the nervous system, is known to affect the brain, eyes, muscular tissues and subcutaneous tissues. However, it is very rare for patients with ocular cysts to have concomitant cerebral cysts. Also, the dominant clinical manifestation of patients with cerebral cysts is either seizures or headache. We report a patient who presented with acute monocular painless vision loss due to intraocular submacular cysticercosis, who on investigation had multiple cerebral parenchymal cysticercal cysts, but never had any seizures. Although such a vision loss after initiation of antiparasitic treatment has been mentioned previously, acute monocular vision loss as the presenting feature of ocular cysticercosis is rare. We present a brief review of literature along with this case report.

  1. Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

    Science.gov (United States)

    Piao, Jin-Chun; Kim, Shin-Dug

    2017-11-07

    Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

  2. Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

    Directory of Open Access Journals (Sweden)

    Jin-Chun Piao

    2017-11-01

    Full Text Available Simultaneous localization and mapping (SLAM is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

  3. Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

    Science.gov (United States)

    Piao, Jin-Chun; Kim, Shin-Dug

    2017-01-01

    Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method. PMID:29112143

  4. Effect of Monocular Deprivation on Rabbit Neural Retinal Cell Densities.

    Science.gov (United States)

    Mwachaka, Philip Maseghe; Saidi, Hassan; Odula, Paul Ochieng; Mandela, Pamela Idenya

    2015-01-01

    To describe the effect of monocular deprivation on densities of neural retinal cells in rabbits. Thirty rabbits, comprised of 18 subject and 12 control animals, were included and monocular deprivation was achieved through unilateral lid suturing in all subject animals. The rabbits were observed for three weeks. At the end of each week, 6 experimental and 3 control animals were euthanized, their retinas was harvested and processed for light microscopy. Photomicrographs of the retina were taken and imported into FIJI software for analysis. Neural retinal cell densities of deprived eyes were reduced along with increasing period of deprivation. The percentage of reductions were 60.9% (P < 0.001), 41.6% (P = 0.003), and 18.9% (P = 0.326) for ganglion, inner nuclear, and outer nuclear cells, respectively. In non-deprived eyes, cell densities in contrast were increased by 116% (P < 0.001), 52% (P < 0.001) and 59.6% (P < 0.001) in ganglion, inner nuclear, and outer nuclear cells, respectively. In this rabbit model, monocular deprivation resulted in activity-dependent changes in cell densities of the neural retina in favour of the non-deprived eye along with reduced cell densities in the deprived eye.

  5. Image-based occupancy sensor

    Science.gov (United States)

    Polese, Luigi Gentile; Brackney, Larry

    2015-05-19

    An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generates an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.

  6. Microprocessor based image processing system

    International Nuclear Information System (INIS)

    Mirza, M.I.; Siddiqui, M.N.; Rangoonwala, A.

    1987-01-01

    Rapid developments in the production of integrated circuits and introduction of sophisticated 8,16 and now 32 bit microprocessor based computers, have set new trends in computer applications. Nowadays the users by investing much less money can make optimal use of smaller systems by getting them custom-tailored according to their requirements. During the past decade there have been great advancements in the field of computer Graphics and consequently, 'Image Processing' has emerged as a separate independent field. Image Processing is being used in a number of disciplines. In the Medical Sciences, it is used to construct pseudo color images from computer aided tomography (CAT) or positron emission tomography (PET) scanners. Art, advertising and publishing people use pseudo colours in pursuit of more effective graphics. Structural engineers use Image Processing to examine weld X-rays to search for imperfections. Photographers use Image Processing for various enhancements which are difficult to achieve in a conventional dark room. (author)

  7. Evidence based medical imaging (EBMI)

    International Nuclear Information System (INIS)

    Smith, Tony

    2008-01-01

    Background: The evidence based paradigm was first described about a decade ago. Previous authors have described a framework for the application of evidence based medicine which can be readily adapted to medical imaging practice. Purpose: This paper promotes the application of the evidence based framework in both the justification of the choice of examination type and the optimisation of the imaging technique used. Methods: The framework includes five integrated steps: framing a concise clinical question; searching for evidence to answer that question; critically appraising the evidence; applying the evidence in clinical practice; and, evaluating the use of revised practices. Results: This paper illustrates the use of the evidence based framework in medical imaging (that is, evidence based medical imaging) using the examples of two clinically relevant case studies. In doing so, a range of information technology and other resources available to medical imaging practitioners are identified with the intention of encouraging the application of the evidence based paradigm in radiography and radiology. Conclusion: There is a perceived need for radiographers and radiologists to make greater use of valid research evidence from the literature to inform their clinical practice and thus provide better quality services

  8. Real Time 3D Facial Movement Tracking Using a Monocular Camera

    Directory of Open Access Journals (Sweden)

    Yanchao Dong

    2016-07-01

    Full Text Available The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference.

  9. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal [Albuquerque, NM

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  10. Monocular Vision System for Fixed Altitude Flight of Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Kuo-Lung Huang

    2015-07-01

    Full Text Available The fastest and most economical method of acquiring terrain images is aerial photography. The use of unmanned aerial vehicles (UAVs has been investigated for this task. However, UAVs present a range of challenges such as flight altitude maintenance. This paper reports a method that combines skyline detection with a stereo vision algorithm to enable the flight altitude of UAVs to be maintained. A monocular camera is mounted on the downside of the aircraft’s nose to collect continuous ground images, and the relative altitude is obtained via a stereo vision algorithm from the velocity of the UAV. Image detection is used to obtain terrain images, and to measure the relative altitude from the ground to the UAV. The UAV flight system can be set to fly at a fixed and relatively low altitude to obtain the same resolution of ground images. A forward-looking camera is mounted on the upside of the aircraft’s nose. In combination with the skyline detection algorithm, this helps the aircraft to maintain a stable flight pattern. Experimental results show that the proposed system enables UAVs to obtain terrain images at constant resolution, and to detect the relative altitude along the flight path.

  11. A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    2015-03-01

    Full Text Available A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance.

  12. Decrease in monocular sleep after sleep deprivation in the domestic chicken

    NARCIS (Netherlands)

    Boerema, AS; Riedstra, B; Strijkstra, AM

    2003-01-01

    We investigated the trade-off between sleep need and alertness, by challenging chickens to modify their monocular sleep. We sleep deprived domestic chickens (Gallus domesticus) to increase their sleep need. We found that in response to sleep deprivation the fraction of monocular sleep within sleep

  13. Action Control: Independent Effects of Memory and Monocular Viewing on Reaching Accuracy

    Science.gov (United States)

    Westwood, D.A.; Robertson, C.; Heath, M.

    2005-01-01

    Evidence suggests that perceptual networks in the ventral visual pathway are necessary for action control when targets are viewed with only one eye, or when the target must be stored in memory. We tested whether memory-linked (i.e., open-loop versus memory-guided actions) and monocular-linked effects (i.e., binocular versus monocular actions) on…

  14. Anisometropia and ptosis in patients with monocular elevation deficiency

    International Nuclear Information System (INIS)

    Zafar, S.N.; Islam, F.; Khan, A.M.

    2016-01-01

    Objective: To determine the effect of ptosis on the refractive error in eyes having monocular elevation deficiency Place and Duration of Study: Al-Shifa Trust Eye Hospital, Rawalpindi, from January 2011 to January 2014. Methodology: Visual acuity, refraction, orthoptic assessment and ptosis evaluation of all patients having monocular elevation deficiency (MED) were recorded. Shapiro-Wilk test was used for tests of normality. Median and interquartile range (IQR) was calculated for the data. Non-parametric variables were compared, using the Wilcoxon signed ranks test. P-values of <0.05 were considered significant. Results: A total of of 41 MED patients were assessed during the study period. Best corrected visual acuity (BCVA) and refractive error was compared between the eyes having MED and the unaffected eyes of the same patient. The refractive status of patients having ptosis with MED were also compared with those having MED without ptosis. Astigmatic correction and vision had significant difference between both the eyes of the patients. Vision was significantly different between the two eyes of patients in both the groups having either presence or absence of ptosis (p=0.04 and p < 0.001, respectively). Conclusion: Significant difference in vision and anisoastigmatism was noted between the two eyes of patients with MED in this study. The presence or absence of ptosis affected the vision but did not have a significant effect on the spherical equivalent (SE) and astigmatic correction between both the eyes. (author)

  15. Image inpainting based on stacked autoencoders

    International Nuclear Information System (INIS)

    Shcherbakov, O; Batishcheva, V

    2014-01-01

    Recently we have proposed the algorithm for the problem of image inpaiting (filling in occluded or damaged parts of images). This algorithm was based on the criterion spectrum entropy and showed promising results despite of using hand-crafted representation of images. In this paper, we present a method for solving image inpaiting task based on learning some image representation. Some results are shown to illustrate quality of image reconstruction.

  16. Monocular display unit for 3D display with correct depth perception

    Science.gov (United States)

    Sakamoto, Kunio; Hosomi, Takashi

    2009-11-01

    A study of virtual-reality system has been popular and its technology has been applied to medical engineering, educational engineering, a CAD/CAM system and so on. The 3D imaging display system has two types in the presentation method; one is a 3-D display system using a special glasses and the other is the monitor system requiring no special glasses. A liquid crystal display (LCD) recently comes into common use. It is possible for this display unit to provide the same size of displaying area as the image screen on the panel. A display system requiring no special glasses is useful for a 3D TV monitor, but this system has demerit such that the size of a monitor restricts the visual field for displaying images. Thus the conventional display can show only one screen, but it is impossible to enlarge the size of a screen, for example twice. To enlarge the display area, the authors have developed an enlarging method of display area using a mirror. Our extension method enables the observers to show the virtual image plane and to enlarge a screen area twice. In the developed display unit, we made use of an image separating technique using polarized glasses, a parallax barrier or a lenticular lens screen for 3D imaging. The mirror can generate the virtual image plane and it enlarges a screen area twice. Meanwhile the 3D display system using special glasses can also display virtual images over a wide area. In this paper, we present a monocular 3D vision system with accommodation mechanism, which is useful function for perceiving depth.

  17. Monocular Visual Deprivation Suppresses Excitability in Adult Human Visual Cortex

    DEFF Research Database (Denmark)

    Lou, Astrid Rosenstand; Madsen, Kristoffer Hougaard; Paulson, Olaf Bjarne

    2011-01-01

    The adult visual cortex maintains a substantial potential for plasticity in response to a change in visual input. For instance, transcranial magnetic stimulation (TMS) studies have shown that binocular deprivation (BD) increases the cortical excitability for inducing phosphenes with TMS. Here, we...... of visual deprivation has a substantial impact on experience-dependent plasticity of the human visual cortex.......The adult visual cortex maintains a substantial potential for plasticity in response to a change in visual input. For instance, transcranial magnetic stimulation (TMS) studies have shown that binocular deprivation (BD) increases the cortical excitability for inducing phosphenes with TMS. Here, we...... employed TMS to trace plastic changes in adult visual cortex before, during, and after 48 h of monocular deprivation (MD) of the right dominant eye. In healthy adult volunteers, MD-induced changes in visual cortex excitability were probed with paired-pulse TMS applied to the left and right occipital cortex...

  18. Monocular oral reading after treatment of dense congenital unilateral cataract

    Science.gov (United States)

    Birch, Eileen E.; Cheng, Christina; Christina, V; Stager, David R.

    2010-01-01

    Background Good long-term visual acuity outcomes for children with dense congenital unilateral cataracts have been reported following early surgery and good compliance with postoperative amblyopia therapy. However, treated eyes rarely achieve normal visual acuity and there has been no formal evaluation of the utility of the treated eye for reading. Methods Eighteen children previously treated for dense congenital unilateral cataract were tested monocularly with the Gray Oral Reading Test, 4th edition (GORT-4) at 7 to 13 years of age using two passages for each eye, one at grade level and one at +1 above grade level. In addition, right eyes of 55 normal children age 7 to 13 served as a control group. The GORT-4 assesses reading rate, accuracy, fluency, and comprehension. Results Visual acuity of treated eyes ranged from 0.1 to 2.0 logMAR and of fellow eyes from −0.1 to 0.2 logMAR. Treated eyes scored significantly lower than fellow and normal control eyes on all scales at grade level and at +1 above grade level. Monocular reading rate, accuracy, fluency, and comprehension were correlated with visual acuity of treated eyes (rs = −0.575 to −0.875, p < 0.005). Treated eyes with 0.1-0.3 logMAR visual acuity did not differ from fellow or normal control eyes in rate, accuracy, fluency, or comprehension when reading at grade level or at +1 above grade level. Fellow eyes did not differ from normal controls on any reading scale. Conclusions Excellent visual acuity outcomes following treatment of dense congenital unilateral cataracts are associated with normal reading ability of the treated eye in school-age children. PMID:20603057

  19. Image matching navigation based on fuzzy information

    Institute of Scientific and Technical Information of China (English)

    田玉龙; 吴伟仁; 田金文; 柳健

    2003-01-01

    In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

  20. Visual Servo Tracking Control of a Wheeled Mobile Robot with a Monocular Fixed Camera

    National Research Council Canada - National Science Library

    Chen, J; Dixon, W. E; Dawson, D. M; Chitrakaran, V. K

    2004-01-01

    In this paper, a visual servo tracking controller for a wheeled mobile robot (WMR) is developed that utilizes feedback from a monocular camera system that is mounted with a fixed position and orientation...

  1. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    Science.gov (United States)

    Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

    2015-02-01

    A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

  2. Ergonomic evaluation of ubiquitous computing with monocular head-mounted display

    Science.gov (United States)

    Kawai, Takashi; Häkkinen, Jukka; Yamazoe, Takashi; Saito, Hiroko; Kishi, Shinsuke; Morikawa, Hiroyuki; Mustonen, Terhi; Kaistinen, Jyrki; Nyman, Göte

    2010-01-01

    In this paper, the authors conducted an experiment to evaluate the UX in an actual outdoor environment, assuming the casual use of monocular HMD to view video content while short walking. In conducting the experiment, eight subjects were asked to view news videos on a monocular HMD while walking through a large shopping mall. Two types of monocular HMDs and a hand-held media player were used, and the psycho-physiological responses of the subjects were measured before, during, and after the experiment. The VSQ, SSQ and NASA-TLX were used to assess the subjective workloads and symptoms. The objective indexes were heart rate and stride and a video recording of the environment in front of the subject's face. The results revealed differences between the two types of monocular HMDs as well as between the monocular HMDs and other conditions. Differences between the types of monocular HMDs may have been due to screen vibration during walking, and it was considered as a major factor in the UX in terms of the workload. Future experiments to be conducted in other locations will have higher cognitive loads in order to study the performance and the situation awareness to actual and media environments.

  3. SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    A. Sharma

    2015-03-01

    Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

  4. Medical Image Tamper Detection Based on Passive Image Authentication.

    Science.gov (United States)

    Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

    2017-12-01

    Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

  5. A SVD Based Image Complexity Measure

    DEFF Research Database (Denmark)

    Gustafsson, David Karl John; Pedersen, Kim Steenstrup; Nielsen, Mads

    2009-01-01

    Images are composed of geometric structures and texture, and different image processing tools - such as denoising, segmentation and registration - are suitable for different types of image contents. Characterization of the image content in terms of geometric structure and texture is an important...... problem that one is often faced with. We propose a patch based complexity measure, based on how well the patch can be approximated using singular value decomposition. As such the image complexity is determined by the complexity of the patches. The concept is demonstrated on sequences from the newly...... collected DIKU Multi-Scale image database....

  6. Chromatic and achromatic monocular deprivation produce separable changes of eye dominance in adults.

    Science.gov (United States)

    Zhou, Jiawei; Reynaud, Alexandre; Kim, Yeon Jin; Mullen, Kathy T; Hess, Robert F

    2017-11-29

    Temporarily depriving one eye of its input, in whole or in part, results in a transient shift in eye dominance in human adults, with the patched eye becoming stronger and the unpatched eye weaker. However, little is known about the role of colour contrast in these behavioural changes. Here, we first show that the changes in eye dominance and contrast sensitivity induced by monocular eye patching affect colour and achromatic contrast sensitivity equally. We next use dichoptic movies, customized and filtered to stimulate the two eyes differentially. We show that a strong imbalance in achromatic contrast between the eyes, with no colour content, also produces similar, unselective shifts in eye dominance for both colour and achromatic contrast sensitivity. Interestingly, if this achromatic imbalance is paired with similar colour contrast in both eyes, the shift in eye dominance is selective, affecting achromatic but not chromatic contrast sensitivity and revealing a dissociation in eye dominance for colour and achromatic image content. On the other hand, a strong imbalance in chromatic contrast between the eyes, with no achromatic content, produces small, unselective changes in eye dominance, but if paired with similar achromatic contrast in both eyes, no changes occur. We conclude that perceptual changes in eye dominance are strongly driven by interocular imbalances in achromatic contrast, with colour contrast having a significant counter balancing effect. In the short term, eyes can have different dominances for achromatic and chromatic contrast, suggesting separate pathways at the site of these neuroplastic changes. © 2017 The Author(s).

  7. CONTEXT BASED FOOD IMAGE ANALYSIS

    OpenAIRE

    He, Ye; Xu, Chang; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

    2013-01-01

    We are developing a dietary assessment system that records daily food intake through the use of food images. Recognizing food in an image is difficult due to large visual variance with respect to eating or preparation conditions. This task becomes even more challenging when different foods have similar visual appearance. In this paper we propose to incorporate two types of contextual dietary information, food co-occurrence patterns and personalized learning models, in food image analysis to r...

  8. ADVANCED CLUSTER BASED IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    D. Kesavaraja

    2011-11-01

    Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

  9. Biometric image enhancement using decision rule based image fusion techniques

    Science.gov (United States)

    Sagayee, G. Mary Amirtha; Arumugam, S.

    2010-02-01

    Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

  10. Pc-Based Floating Point Imaging Workstation

    Science.gov (United States)

    Guzak, Chris J.; Pier, Richard M.; Chinn, Patty; Kim, Yongmin

    1989-07-01

    The medical, military, scientific and industrial communities have come to rely on imaging and computer graphics for solutions to many types of problems. Systems based on imaging technology are used to acquire and process images, and analyze and extract data from images that would otherwise be of little use. Images can be transformed and enhanced to reveal detail and meaning that would go undetected without imaging techniques. The success of imaging has increased the demand for faster and less expensive imaging systems and as these systems become available, more and more applications are discovered and more demands are made. From the designer's perspective the challenge to meet these demands forces him to attack the problem of imaging from a different perspective. The computing demands of imaging algorithms must be balanced against the desire for affordability and flexibility. Systems must be flexible and easy to use, ready for current applications but at the same time anticipating new, unthought of uses. Here at the University of Washington Image Processing Systems Lab (IPSL) we are focusing our attention on imaging and graphics systems that implement imaging algorithms for use in an interactive environment. We have developed a PC-based imaging workstation with the goal to provide powerful and flexible, floating point processing capabilities, along with graphics functions in an affordable package suitable for diverse environments and many applications.

  11. Developing stereo image based robot control system

    Energy Technology Data Exchange (ETDEWEB)

    Suprijadi,; Pambudi, I. R.; Woran, M.; Naa, C. F; Srigutomo, W. [Department of Physics, FMIPA, InstitutTeknologi Bandung Jl. Ganesha No. 10. Bandung 40132, Indonesia supri@fi.itb.ac.id (Indonesia)

    2015-04-16

    Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based on stereovision captures.

  12. Detail Enhancement for Infrared Images Based on Propagated Image Filter

    Directory of Open Access Journals (Sweden)

    Yishu Peng

    2016-01-01

    Full Text Available For displaying high-dynamic-range images acquired by thermal camera systems, 14-bit raw infrared data should map into 8-bit gray values. This paper presents a new method for detail enhancement of infrared images to display the image with a relatively satisfied contrast and brightness, rich detail information, and no artifacts caused by the image processing. We first adopt a propagated image filter to smooth the input image and separate the image into the base layer and the detail layer. Then, we refine the base layer by using modified histogram projection for compressing. Meanwhile, the adaptive weights derived from the layer decomposition processing are used as the strict gain control for the detail layer. The final display result is obtained by recombining the two modified layers. Experimental results on both cooled and uncooled infrared data verify that the proposed method outperforms the method based on log-power histogram modification and bilateral filter-based detail enhancement in both detail enhancement and visual effect.

  13. Dichoptic training in adults with amblyopia: Additional stereoacuity gains over monocular training.

    Science.gov (United States)

    Liu, Xiang-Yun; Zhang, Jun-Yun

    2017-08-04

    Dichoptic training is a recent focus of research on perceptual learning in adults with amblyopia, but whether and how dichoptic training is superior to traditional monocular training is unclear. Here we investigated whether dichoptic training could further boost visual acuity and stereoacuity in monocularly well-trained adult amblyopic participants. During dichoptic training the participants used the amblyopic eye to practice a contrast discrimination task, while a band-filtered noise masker was simultaneously presented in the non-amblyopic fellow eye. Dichoptic learning was indexed by the increase of maximal tolerable noise contrast for successful contrast discrimination in the amblyopic eye. The results showed that practice tripled maximal tolerable noise contrast in 13 monocularly well-trained amblyopic participants. Moreover, the training further improved stereoacuity by 27% beyond the 55% gain from previous monocular training, but unchanged visual acuity of the amblyopic eyes. Therefore our dichoptic training method may produce extra gains of stereoacuity, but not visual acuity, in adults with amblyopia after monocular training. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Image Based Rendering and Virtual Reality

    DEFF Research Database (Denmark)

    Livatino, Salvatore

    The Presentation concerns with an overview of Image Based Rendering approaches and their use on Virtual Reality, including Virtual Photography and Cinematography, and Mobile Robot Navigation.......The Presentation concerns with an overview of Image Based Rendering approaches and their use on Virtual Reality, including Virtual Photography and Cinematography, and Mobile Robot Navigation....

  15. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  16. Content Based Image Matching for Planetary Science

    Science.gov (United States)

    Deans, M. C.; Meyer, C.

    2006-12-01

    Planetary missions generate large volumes of data. With the MER rovers still functioning on Mars, PDS contains over 7200 released images from the Microscopic Imagers alone. These data products are only searchable by keys such as the Sol, spacecraft clock, or rover motion counter index, with little connection to the semantic content of the images. We have developed a method for matching images based on the visual textures in images. For every image in a database, a series of filters compute the image response to localized frequencies and orientations. Filter responses are turned into a low dimensional descriptor vector, generating a 37 dimensional fingerprint. For images such as the MER MI, this represents a compression ratio of 99.9965% (the fingerprint is approximately 0.0035% the size of the original image). At query time, fingerprints are quickly matched to find images with similar appearance. Image databases containing several thousand images are preprocessed offline in a matter of hours. Image matches from the database are found in a matter of seconds. We have demonstrated this image matching technique using three sources of data. The first database consists of 7200 images from the MER Microscopic Imager. The second database consists of 3500 images from the Narrow Angle Mars Orbital Camera (MOC-NA), which were cropped into 1024×1024 sub-images for consistency. The third database consists of 7500 scanned archival photos from the Apollo Metric Camera. Example query results from all three data sources are shown. We have also carried out user tests to evaluate matching performance by hand labeling results. User tests verify approximately 20% false positive rate for the top 14 results for MOC NA and MER MI data. This means typically 10 to 12 results out of 14 match the query image sufficiently. This represents a powerful search tool for databases of thousands of images where the a priori match probability for an image might be less than 1%. Qualitatively, correct

  17. Image magnification based on similarity analogy

    International Nuclear Information System (INIS)

    Chen Zuoping; Ye Zhenglin; Wang Shuxun; Peng Guohua

    2009-01-01

    Aiming at the high time complexity of the decoding phase in the traditional image enlargement methods based on fractal coding, a novel image magnification algorithm is proposed in this paper, which has the advantage of iteration-free decoding, by using the similarity analogy between an image and its zoom-out and zoom-in. A new pixel selection technique is also presented to further improve the performance of the proposed method. Furthermore, by combining some existing fractal zooming techniques, an efficient image magnification algorithm is obtained, which can provides the image quality as good as the state of the art while greatly decrease the time complexity of the decoding phase.

  18. Content-Based Image Retrial Based on Hadoop

    Directory of Open Access Journals (Sweden)

    DongSheng Yin

    2013-01-01

    Full Text Available Generally, time complexity of algorithms for content-based image retrial is extremely high. In order to retrieve images on large-scale databases efficiently, a new way for retrieving based on Hadoop distributed framework is proposed. Firstly, a database of images features is built by using Speeded Up Robust Features algorithm and Locality-Sensitive Hashing and then perform the search on Hadoop platform in a parallel way specially designed. Considerable experimental results show that it is able to retrieve images based on content on large-scale cluster and image sets effectively.

  19. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia.

    Science.gov (United States)

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-02-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n = 13) were asked to complete two psychophysical supra-threshold binocular summation tasks: (1) binocular phase combination and (2) dichoptic global motion coherence before and after monocular training to investigate this question. We showed that these participants benefited from monocular training in terms of binocular combination. More importantly, the improvements observed with the area under log CSF (AULCSF) were found to be correlated with the improvements in binocular phase combination.

  20. Retinal image quality assessment based on image clarity and content

    Science.gov (United States)

    Abdel-Hamid, Lamiaa; El-Rafei, Ahmed; El-Ramly, Salwa; Michelson, Georg; Hornegger, Joachim

    2016-09-01

    Retinal image quality assessment (RIQA) is an essential step in automated screening systems to avoid misdiagnosis caused by processing poor quality retinal images. A no-reference transform-based RIQA algorithm is introduced that assesses images based on five clarity and content quality issues: sharpness, illumination, homogeneity, field definition, and content. Transform-based RIQA algorithms have the advantage of considering retinal structures while being computationally inexpensive. Wavelet-based features are proposed to evaluate the sharpness and overall illumination of the images. A retinal saturation channel is designed and used along with wavelet-based features for homogeneity assessment. The presented sharpness and illumination features are utilized to assure adequate field definition, whereas color information is used to exclude nonretinal images. Several publicly available datasets of varying quality grades are utilized to evaluate the feature sets resulting in area under the receiver operating characteristic curve above 0.99 for each of the individual feature sets. The overall quality is assessed by a classifier that uses the collective features as an input vector. The classification results show superior performance of the algorithm in comparison to other methods from literature. Moreover, the algorithm addresses efficiently and comprehensively various quality issues and is suitable for automatic screening systems.

  1. Image content authentication based on channel coding

    Science.gov (United States)

    Zhang, Fan; Xu, Lei

    2008-03-01

    The content authentication determines whether an image has been tampered or not, and if necessary, locate malicious alterations made on the image. Authentication on a still image or a video are motivated by recipient's interest, and its principle is that a receiver must be able to identify the source of this document reliably. Several techniques and concepts based on data hiding or steganography designed as a means for the image authentication. This paper presents a color image authentication algorithm based on convolution coding. The high bits of color digital image are coded by the convolution codes for the tamper detection and localization. The authentication messages are hidden in the low bits of image in order to keep the invisibility of authentication. All communications channels are subject to errors introduced because of additive Gaussian noise in their environment. Data perturbations cannot be eliminated but their effect can be minimized by the use of Forward Error Correction (FEC) techniques in the transmitted data stream and decoders in the receiving system that detect and correct bits in error. This paper presents a color image authentication algorithm based on convolution coding. The message of each pixel is convolution encoded with the encoder. After the process of parity check and block interleaving, the redundant bits are embedded in the image offset. The tamper can be detected and restored need not accessing the original image.

  2. Optical image hiding based on interference

    Science.gov (United States)

    Zhang, Yan; Wang, Bo

    2009-11-01

    Optical image processing has been paid a lot of attentions recently due to its large capacitance and fast speed. Many image encryption and hiding technologies have been proposed based on the optical technology. In conventional image encryption methods, the random phase masks are usually used as encryption keys to encode the images into random white noise distribution. However, this kind of methods requires interference technology such as holography to record complex amplitude. Furthermore, it is vulnerable to attack techniques. The image hiding methods employ the phase retrieve algorithm to encode the images into two or more phase masks. The hiding process is carried out within a computer and the images are reconstructed optically. But the iterative algorithms need a lot of time to hide the image into the masks. All methods mentioned above are based on the optical diffraction of the phase masks. In this presentation, we will propose a new optical image hiding method based on interference. The coherence lights pass through two phase masks and are combined by a beam splitter. Two beams interfere with each other and the desired image appears at the pre-designed plane. Two phase distribution masks are designed analytically; therefore, the hiding speed can be obviously improved. Simulation results are carried out to demonstrate the validity of the new proposed methods.

  3. An overview of medical image data base

    International Nuclear Information System (INIS)

    Nishihara, Eitaro

    1992-01-01

    Recently, the systematization using computers in medical institutions has advanced, and the introduction of hospital information system has been almost completed in the large hospitals with more than 500 beds. But the objects of the management of the hospital information system are text information, and do not include the management of images of enormous quantity. By the progress of image diagnostic equipment, the digitization of medical images has advanced, but the management of images in hospitals does not utilize the merits of digital images. For the purpose of solving these problems, the picture archiving and communication system (PACS) was proposed about ten years ago, which makes medical images into a data base, and enables the on-line access to images from various places in hospitals. The studies have been continued to realize it. The features of medical image data, the present status of utilizing medical image data, the outline of the PACS, the image data base for the PACS, the problems in the realization of the data base and the technical trend, and the state of actual construction of the PACS are reported. (K.I.)

  4. Characterization of lens based photoacoustic imaging system

    Directory of Open Access Journals (Sweden)

    Kalloor Joseph Francis

    2017-12-01

    Full Text Available Some of the challenges in translating photoacoustic (PA imaging to clinical applications includes limited view of the target tissue, low signal to noise ratio and the high cost of developing real-time systems. Acoustic lens based PA imaging systems, also known as PA cameras are a potential alternative to conventional imaging systems in these scenarios. The 3D focusing action of lens enables real-time C-scan imaging with a 2D transducer array. In this paper, we model the underlying physics in a PA camera in the mathematical framework of an imaging system and derive a closed form expression for the point spread function (PSF. Experimental verification follows including the details on how to design and fabricate the lens inexpensively. The system PSF is evaluated over a 3D volume that can be imaged by this PA camera. Its utility is demonstrated by imaging phantom and an ex vivo human prostate tissue sample.

  5. Characterization of lens based photoacoustic imaging system.

    Science.gov (United States)

    Francis, Kalloor Joseph; Chinni, Bhargava; Channappayya, Sumohana S; Pachamuthu, Rajalakshmi; Dogra, Vikram S; Rao, Navalgund

    2017-12-01

    Some of the challenges in translating photoacoustic (PA) imaging to clinical applications includes limited view of the target tissue, low signal to noise ratio and the high cost of developing real-time systems. Acoustic lens based PA imaging systems, also known as PA cameras are a potential alternative to conventional imaging systems in these scenarios. The 3D focusing action of lens enables real-time C-scan imaging with a 2D transducer array. In this paper, we model the underlying physics in a PA camera in the mathematical framework of an imaging system and derive a closed form expression for the point spread function (PSF). Experimental verification follows including the details on how to design and fabricate the lens inexpensively. The system PSF is evaluated over a 3D volume that can be imaged by this PA camera. Its utility is demonstrated by imaging phantom and an ex vivo human prostate tissue sample.

  6. ROV Based Underwater Blurred Image Restoration

    Institute of Scientific and Technical Information of China (English)

    LIU Zhishen; DING Tianfu; WANG Gang

    2003-01-01

    In this paper, we present a method of ROV based image processing to restore underwater blurry images from the theory of light and image transmission in the sea. Computer is used to simulate the maximum detection range of the ROV under different water body conditions. The receiving irradiance of the video camera at different detection ranges is also calculated. The ROV's detection performance under different water body conditions is given by simulation. We restore the underwater blurry images using the Wiener filter based on the simulation. The Wiener filter is shown to be a simple useful method for underwater image restoration in the ROV underwater experiments. We also present examples of restored images of an underwater standard target taken by the video camera in these experiments.

  7. Understanding images using knowledge based approach

    International Nuclear Information System (INIS)

    Tascini, G.

    1985-01-01

    This paper presents an approach to image understanding focusing on low level image processing and proposes a rule-based approach as part of larger knowledge-based system. The general system has a yerarchical structure that comprises several knowledge-based layers. The main idea is to confine at the lower level the domain independent knowledge and to reserve the higher levels for the domain dependent knowledge, that is for the interpretation

  8. Pediatric Oculomotor Findings during Monocular Videonystagmography: A Developmental Study.

    Science.gov (United States)

    Doettl, Steven M; Plyler, Patrick N; McCaslin, Devin L; Schay, Nancy L

    2015-09-01

    The differential diagnosis of a dizzy patient >4 yrs old is often aided by videonystagmography (VNG) testing to provide a global assessment of peripheral and central vestibular function. Although the value of a VNG evaluation is well-established, it remains unclear if the VNG test battery is as applicable to the pediatric population as it is for adults. Oculomotor testing specifically, as opposed to spontaneous, positional, and caloric testing, is dependent upon neurologic function. Thus, age and corresponding neuromaturation may have a significant effect on oculomotor findings. The purpose of this investigation was to describe the effect of age on various tests of oculomotor function during a monocular VNG examination. Specifically, this study systematically characterized the impact of age on saccade tracking, smooth pursuit tracking, and optokinetic (OPK) nystagmus. The present study used a prospective, repeated measures design. A total of 62 healthy participants were evaluated. Group 1 consisted of 29 4- to 6-yr-olds. Group 2 consisted of 33 21- to 44-yr-olds. Each participant completed a standard VNG oculomotor test battery including saccades, smooth pursuit, and OPK testing in randomized order using a commercially available system. The response metrics saccade latency, accuracy, and speed, smooth pursuit gain, OPK nystagmus gain, speed and asymmetry ratios were collected and analyzed. Significant differences were noted between groups for saccade latency, smooth pursuit gain, and OPK asymmetry ratios. Saccade latency was significantly longer for the pediatric participants compared to the adult participants. Smooth pursuit gain was significantly less for the pediatric participants compared to the adult participants. The pediatric participants also demonstrated increased OPK asymmetry ratios compared to the adult participants. Significant differences were noted between the pediatric and adult participants for saccade latency, smooth pursuit gain, and OPK

  9. Image-based petrophysical parameters

    DEFF Research Database (Denmark)

    Noe-Nygaard, Jakob; Engstrøm, Finn; Sølling, Theis Ivan

    2017-01-01

    run directly from the micro-CT results on a cutting measured on an in-house instrument; the results clearly show that micro-CT measurements on chalk do not capture the pore space with sufficient detail to be predictive. Overall, with the appropriate resolution, the present study shows......-computed-tomography (nano-CT) images of trim sections and cuttings. Moreover, the trim-section results are upscaled to trim size to form the basis of an additional comparison. The results are also benchmarked against conventional core analysis (CCAL) results on trim-size samples. The comparison shows that petrophysical...... parameters from CT imaging agree reasonably well with those determined experimentally. The upscaled results show some discrepancy with the nano-CT results, particularly in the case of the low-permeability plug. This is probably because of the challenge in finding a representative subvolume. For the cuttings...

  10. A geometric method for computing ocular kinematics and classifying gaze events using monocular remote eye tracking in a robotic environment.

    Science.gov (United States)

    Singh, Tarkeshwar; Perry, Christopher M; Herter, Troy M

    2016-01-26

    Robotic and virtual-reality systems offer tremendous potential for improving assessment and rehabilitation of neurological disorders affecting the upper extremity. A key feature of these systems is that visual stimuli are often presented within the same workspace as the hands (i.e., peripersonal space). Integrating video-based remote eye tracking with robotic and virtual-reality systems can provide an additional tool for investigating how cognitive processes influence visuomotor learning and rehabilitation of the upper extremity. However, remote eye tracking systems typically compute ocular kinematics by assuming eye movements are made in a plane with constant depth (e.g. frontal plane). When visual stimuli are presented at variable depths (e.g. transverse plane), eye movements have a vergence component that may influence reliable detection of gaze events (fixations, smooth pursuits and saccades). To our knowledge, there are no available methods to classify gaze events in the transverse plane for monocular remote eye tracking systems. Here we present a geometrical method to compute ocular kinematics from a monocular remote eye tracking system when visual stimuli are presented in the transverse plane. We then use the obtained kinematics to compute velocity-based thresholds that allow us to accurately identify onsets and offsets of fixations, saccades and smooth pursuits. Finally, we validate our algorithm by comparing the gaze events computed by the algorithm with those obtained from the eye-tracking software and manual digitization. Within the transverse plane, our algorithm reliably differentiates saccades from fixations (static visual stimuli) and smooth pursuits from saccades and fixations when visual stimuli are dynamic. The proposed methods provide advancements for examining eye movements in robotic and virtual-reality systems. Our methods can also be used with other video-based or tablet-based systems in which eye movements are performed in a peripersonal

  11. Image based rendering of iterated function systems

    NARCIS (Netherlands)

    Wijk, van J.J.; Saupe, D.

    2004-01-01

    A fast method to generate fractal imagery is presented. Iterated function systems (IFS) are based on repeatedly copying transformed images. We show that this can be directly translated into standard graphics operations: Each image is generated by texture mapping and blending copies of the previous

  12. Infrared Imaging for Inquiry-Based Learning

    Science.gov (United States)

    Xie, Charles; Hazzard, Edmund

    2011-01-01

    Based on detecting long-wavelength infrared (IR) radiation emitted by the subject, IR imaging shows temperature distribution instantaneously and heat flow dynamically. As a picture is worth a thousand words, an IR camera has great potential in teaching heat transfer, which is otherwise invisible. The idea of using IR imaging in teaching was first…

  13. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  14. Image based Monument Recognition using Graph based Visual Saliency

    DEFF Research Database (Denmark)

    Kalliatakis, Grigorios; Triantafyllidis, Georgios

    2013-01-01

    This article presents an image-based application aiming at simple image classification of well-known monuments in the area of Heraklion, Crete, Greece. This classification takes place by utilizing Graph Based Visual Saliency (GBVS) and employing Scale Invariant Feature Transform (SIFT) or Speeded......, the images have been previously processed according to the Graph Based Visual Saliency model in order to keep either SIFT or SURF features corresponding to the actual monuments while the background “noise” is minimized. The application is then able to classify these images, helping the user to better...

  15. Comic image understanding based on polygon detection

    Science.gov (United States)

    Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong

    2013-01-01

    Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.

  16. Fast single image dehazing based on image fusion

    Science.gov (United States)

    Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

    2015-01-01

    Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

  17. Image denoising based on noise detection

    Science.gov (United States)

    Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

    2018-03-01

    Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

  18. Distance and velocity estimation using optical flow from a monocular camera

    NARCIS (Netherlands)

    Ho, H.W.; de Croon, G.C.H.E.; Chu, Q.

    2016-01-01

    Monocular vision is increasingly used in Micro Air Vehicles for navigation. In particular, optical flow, inspired by flying insects, is used to perceive vehicles’ movement with respect to the surroundings or sense changes in the environment. However, optical flow does not directly provide us the

  19. Distance and velocity estimation using optical flow from a monocular camera

    NARCIS (Netherlands)

    Ho, H.W.; de Croon, G.C.H.E.; Chu, Q.

    2017-01-01

    Monocular vision is increasingly used in micro air vehicles for navigation. In particular, optical flow, inspired by flying insects, is used to perceive vehicle movement with respect to the surroundings or sense changes in the environment. However, optical flow does not directly provide us the

  20. Three dimensional monocular human motion analysis in end-effector space

    DEFF Research Database (Denmark)

    Hauberg, Søren; Lapuyade, Jerome; Engell-Nørregård, Morten Pol

    2009-01-01

    In this paper, we present a novel approach to three dimensional human motion estimation from monocular video data. We employ a particle filter to perform the motion estimation. The novelty of the method lies in the choice of state space for the particle filter. Using a non-linear inverse kinemati...

  1. The effects of left and right monocular viewing on hemispheric activation.

    Science.gov (United States)

    Wang, Chao; Burtis, D Brandon; Ding, Mingzhou; Mo, Jue; Williamson, John B; Heilman, Kenneth M

    2018-03-01

    Prior research has revealed that whereas activation of the left hemisphere primarily increases the activity of the parasympathetic division of the autonomic nervous system, right-hemisphere activation increases the activity of the sympathetic division. In addition, each hemisphere primarily receives retinocollicular projections from the contralateral eye. A prior study reported that pupillary dilation was greater with left- than with right-eye monocular viewing. The goal of this study was to test the alternative hypotheses that this asymmetric pupil dilation with left-eye viewing was induced by activation of the right-hemispheric-mediated sympathetic activity, versus a reduction of left-hemisphere-mediated parasympathetic activity. Thus, this study was designed to learn whether there are changes in hemispheric activation, as measured by alteration of spontaneous alpha activity, during right versus left monocular viewing. High-density electroencephalography (EEG) was recorded from healthy participants viewing a crosshair with their right, left, or both eyes. There was a significantly less alpha power over the right hemisphere's parietal-occipital area with left and binocular viewing than with right-eye monocular viewing. The greater relative reduction of right-hemisphere alpha activity during left than during right monocular viewing provides further evidence that left-eye viewing induces greater increase in right-hemisphere activation than does right-eye viewing.

  2. Monocular zones in stereoscopic scenes: A useful source of information for human binocular vision?

    Science.gov (United States)

    Harris, Julie M.

    2010-02-01

    When an object is closer to an observer than the background, the small differences between right and left eye views are interpreted by the human brain as depth. This basic ability of the human visual system, called stereopsis, lies at the core of all binocular three-dimensional (3-D) perception and related technological display development. To achieve stereopsis, it is traditionally assumed that corresponding locations in the right and left eye's views must first be matched, then the relative differences between right and left eye locations are used to calculate depth. But this is not the whole story. At every object-background boundary, there are regions of the background that only one eye can see because, in the other eye's view, the foreground object occludes that region of background. Such monocular zones do not have a corresponding match in the other eye's view and can thus cause problems for depth extraction algorithms. In this paper I will discuss evidence, from our knowledge of human visual perception, illustrating that monocular zones do not pose problems for our human visual systems, rather, our visual systems can extract depth from such zones. I review the relevant human perception literature in this area, and show some recent data aimed at quantifying the perception of depth from monocular zones. The paper finishes with a discussion of the potential importance of considering monocular zones, for stereo display technology and depth compression algorithms.

  3. LASIK monocular en pacientes adultos con ambliopía por anisometropía

    Directory of Open Access Journals (Sweden)

    Alejandro Tamez-Peña

    2017-09-01

    Conclusiones: La cirugía refractiva monocular en pacientes con ambliopía por anisometropía es una opción terapéutica segura y efectiva que ofrece resultados visuales satisfactorios, preservando o incluso mejorando la AVMC preoperatoria.

  4. Fast detection and modeling of human-body parts from monocular video

    NARCIS (Netherlands)

    Lao, W.; Han, Jungong; With, de P.H.N.; Perales, F.J.; Fisher, R.B.

    2009-01-01

    This paper presents a novel and fast scheme to detect different body parts in human motion. Using monocular video sequences, trajectory estimation and body modeling of moving humans are combined in a co-operating processing architecture. More specifically, for every individual person, features of

  5. A multicore based parallel image registration method.

    Science.gov (United States)

    Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L; Foran, David J

    2009-01-01

    Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform.

  6. An image adaptive, wavelet-based watermarking of digital images

    Science.gov (United States)

    Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia

    2007-12-01

    In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.

  7. A fractal-based image encryption system

    KAUST Repository

    Abd-El-Hafiz, S. K.

    2014-12-01

    This study introduces a novel image encryption system based on diffusion and confusion processes in which the image information is hidden inside the complex details of fractal images. A simplified encryption technique is, first, presented using a single-fractal image and statistical analysis is performed. A general encryption system utilising multiple fractal images is, then, introduced to improve the performance and increase the encryption key up to hundreds of bits. This improvement is achieved through several parameters: feedback delay, multiplexing and independent horizontal or vertical shifts. The effect of each parameter is studied separately and, then, they are combined to illustrate their influence on the encryption quality. The encryption quality is evaluated using different analysis techniques such as correlation coefficients, differential attack measures, histogram distributions, key sensitivity analysis and the National Institute of Standards and Technology (NIST) statistical test suite. The obtained results show great potential compared to other techniques.

  8. PIXEL PATTERN BASED STEGANOGRAPHY ON IMAGES

    Directory of Open Access Journals (Sweden)

    R. Rejani

    2015-02-01

    Full Text Available One of the drawback of most of the existing steganography methods is that it alters the bits used for storing color information. Some of the examples include LSB or MSB based steganography. There are also various existing methods like Dynamic RGB Intensity Based Steganography Scheme, Secure RGB Image Steganography from Pixel Indicator to Triple Algorithm etc that can be used to find out the steganography method used and break it. Another drawback of the existing methods is that it adds noise to the image which makes the image look dull or grainy making it suspicious for a person about existence of a hidden message within the image. To overcome these shortcomings we have come up with a pixel pattern based steganography which involved hiding the message within in image by using the existing RGB values whenever possible at pixel level or with minimum changes. Along with the image a key will also be used to decrypt the message stored at pixel levels. For further protection, both the message stored as well as the key file will be in encrypted format which can have same or different keys or decryption. Hence we call it as a RGB pixel pattern based steganography.

  9. Parallel CT image reconstruction based on GPUs

    International Nuclear Information System (INIS)

    Flores, Liubov A.; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2014-01-01

    In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data. - Highlights: • We developed GPU-based iterative algorithm to reconstruct images. • Iterative algorithms are capable to reconstruct images from under sampled set of projections. • The computer cost of the implementation of the developed algorithm is low. • The efficiency of the algorithm increases for the large scale problems

  10. Intelligent image retrieval based on radiology reports

    Energy Technology Data Exchange (ETDEWEB)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar [University Medical Center Freiburg, Department of Diagnostic Radiology, Freiburg (Germany); Daumke, Philipp; Simon, Kai [Averbis GmbH, Freiburg (Germany)

    2012-12-15

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  11. IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

  12. Composite Techniques Based Color Image Compression

    Directory of Open Access Journals (Sweden)

    Zainab Ibrahim Abood

    2017-03-01

    Full Text Available Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S, composite wavelet technique (W and composite multi-wavelet technique (M. For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM in M technique which has the highest values of energy (En and compression ratio (CR and least values of bit per pixel (bpp, time (T and rate distortion R(D. Also the values of the compression parameters of the color image are nearly the same as the average values of the compression parameters of the three bands of the same image.

  13. Intelligent image retrieval based on radiology reports

    International Nuclear Information System (INIS)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar; Daumke, Philipp; Simon, Kai

    2012-01-01

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  14. [PACS-based endoscope image acquisition workstation].

    Science.gov (United States)

    Liu, J B; Zhuang, T G

    2001-01-01

    A practical PACS-based Endoscope Image Acquisition Workstation is here introduced. By a Multimedia Video Card, the endoscope video is digitized and captured dynamically or statically into computer. This workstation realizes a variety of functions such as the endoscope video's acquisition and display, as well as the editing, processing, managing, storage, printing, communication of related information. Together with other medical image workstation, it can make up the image sources of PACS for hospitals. In addition, it can also act as an independent endoscopy diagnostic system.

  15. Jet-Based Local Image Descriptors

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg

    2012-01-01

    We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on ...

  16. Dialog-based Interactive Image Retrieval

    OpenAIRE

    Guo, Xiaoxiao; Wu, Hui; Cheng, Yu; Rennie, Steven; Feris, Rogerio Schmidt

    2018-01-01

    Existing methods for interactive image retrieval have demonstrated the merit of integrating user feedback, improving retrieval results. However, most current systems rely on restricted forms of user feedback, such as binary relevance responses, or feedback based on a fixed set of relative attributes, which limits their impact. In this paper, we introduce a new approach to interactive image search that enables users to provide feedback via natural language, allowing for more natural and effect...

  17. Average Gait Differential Image Based Human Recognition

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

    Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

  18. Nonlaser-based 3D surface imaging

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.

  19. Neural network based multiscale image restoration approach

    Science.gov (United States)

    de Castro, Ana Paula A.; da Silva, José D. S.

    2007-02-01

    This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.

  20. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  1. Discriminative Projection Selection Based Face Image Hashing

    Science.gov (United States)

    Karabat, Cagatay; Erdogan, Hakan

    Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

  2. LSB Based Quantum Image Steganography Algorithm

    Science.gov (United States)

    Jiang, Nan; Zhao, Na; Wang, Luo

    2016-01-01

    Quantum steganography is the technique which hides a secret message into quantum covers such as quantum images. In this paper, two blind LSB steganography algorithms in the form of quantum circuits are proposed based on the novel enhanced quantum representation (NEQR) for quantum images. One algorithm is plain LSB which uses the message bits to substitute for the pixels' LSB directly. The other is block LSB which embeds a message bit into a number of pixels that belong to one image block. The extracting circuits can regain the secret message only according to the stego cover. Analysis and simulation-based experimental results demonstrate that the invisibility is good, and the balance between the capacity and the robustness can be adjusted according to the needs of applications.

  3. Video-based noncooperative iris image segmentation.

    Science.gov (United States)

    Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

    2011-02-01

    In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

  4. Bayer image parallel decoding based on GPU

    Science.gov (United States)

    Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

    2012-11-01

    In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

  5. HVS-based medical image compression

    Energy Technology Data Exchange (ETDEWEB)

    Kai Xie [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)]. E-mail: xie_kai2001@sjtu.edu.cn; Jie Yang [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China); Min Zhuyue [CREATIS-CNRS Research Unit 5515 and INSERM Unit 630, 69621 Villeurbanne (France); Liang Lixiao [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)

    2005-07-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time.

  6. HVS-based medical image compression

    International Nuclear Information System (INIS)

    Kai Xie; Jie Yang; Min Zhuyue; Liang Lixiao

    2005-01-01

    Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time

  7. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia

    OpenAIRE

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-01-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n?=?13) were asked to complete two psychophysical supra-threshold binoc...

  8. [Acute monocular loss of vision : Differential diagnostic considerations apart from the internistic etiological clarification].

    Science.gov (United States)

    Rickmann, A; Macek, M A; Szurman, P; Boden, K

    2017-08-03

    We report the case of acute painless monocular loss of vision in a 53-year-old man. An interdisciplinary etiological evaluation remained without pathological findings with respect to arterial branch occlusion. A reevaluation of the patient history led to a possible association with the administration of phosphodiesterase type 5 inhibitor (PDE5 inhibitor). A critical review of the literature on PDE5 inhibitor administration with ocular participation was performed.

  9. A Case of Recurrent Transient Monocular Visual Loss after Receiving Sildenafil

    Directory of Open Access Journals (Sweden)

    Asaad Ghanem Ghanem

    2011-01-01

    Full Text Available A 53-year-old man was attended to the Clinic Ophthalmic Center, Mansoura University, Egypt, with recurrent transient monocular visual loss after receiving sildenafil citrate (Viagra for erectile dysfunction. Examination for possible risk factors revealed mild hypercholesterolemia. Family history showed that his father had suffered from bilateral nonarteritic anterior ischemic optic neuropathy (NAION. Physicians might look for arteriosclerotic risk factors and family history of NAION among predisposing risk factors before prescribing sildenafil erectile dysfunction drugs.

  10. Homotopy Based Reconstruction from Acoustic Images

    DEFF Research Database (Denmark)

    Sharma, Ojaswa

    of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...... GPU (Graphics Processing Unit) based methods are suggested for a streaming computation on large volumes of data. Validation of results for acoustic images is not straightforward due to unavailability of ground truth. Accuracy figures for the suggested methods are provided using phantom object...

  11. Autocalibrating vision guided navigation of unmanned air vehicles via tactical monocular cameras in GPS denied environments

    Science.gov (United States)

    Celik, Koray

    This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors.

  12. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

    2009-01-01

    -based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...

  13. Image Coding Based on Address Vector Quantization.

    Science.gov (United States)

    Feng, Yushu

    Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing

  14. Software for medical image based phantom modelling

    International Nuclear Information System (INIS)

    Possani, R.G.; Massicano, F.; Coelho, T.S.; Yoriyaz, H.

    2011-01-01

    Latest treatment planning systems depends strongly on CT images, so the tendency is that the dosimetry procedures in nuclear medicine therapy be also based on images, such as magnetic resonance imaging (MRI) or computed tomography (CT), to extract anatomical and histological information, as well as, functional imaging or activities map as PET or SPECT. This information associated with the simulation of radiation transport software is used to estimate internal dose in patients undergoing treatment in nuclear medicine. This work aims to re-engineer the software SCMS, which is an interface software between the Monte Carlo code MCNP, and the medical images, that carry information from the patient in treatment. In other words, the necessary information contained in the images are interpreted and presented in a specific format to the Monte Carlo MCNP code to perform the simulation of radiation transport. Therefore, the user does not need to understand complex process of inputting data on MCNP, as the SCMS is responsible for automatically constructing anatomical data from the patient, as well as the radioactive source data. The SCMS was originally developed in Fortran- 77. In this work it was rewritten in an object-oriented language (JAVA). New features and data options have also been incorporated into the software. Thus, the new software has a number of improvements, such as intuitive GUI and a menu for the selection of the energy spectra correspondent to a specific radioisotope stored in a XML data bank. The new version also supports new materials and the user can specify an image region of interest for the calculation of absorbed dose. (author)

  15. Fourier transform based scalable image quality measure.

    Science.gov (United States)

    Narwaria, Manish; Lin, Weisi; McLoughlin, Ian; Emmanuel, Sabu; Chia, Liang-Tien

    2012-08-01

    We present a new image quality assessment (IQA) algorithm based on the phase and magnitude of the 2D (twodimensional) Discrete Fourier Transform (DFT). The basic idea is to compare the phase and magnitude of the reference and distorted images to compute the quality score. However, it is well known that the Human Visual Systems (HVSs) sensitivity to different frequency components is not the same. We accommodate this fact via a simple yet effective strategy of nonuniform binning of the frequency components. This process also leads to reduced space representation of the image thereby enabling the reduced-reference (RR) prospects of the proposed scheme. We employ linear regression to integrate the effects of the changes in phase and magnitude. In this way, the required weights are determined via proper training and hence more convincing and effective. Lastly, using the fact that phase usually conveys more information than magnitude, we use only the phase for RR quality assessment. This provides the crucial advantage of further reduction in the required amount of reference image information. The proposed method is therefore further scalable for RR scenarios. We report extensive experimental results using a total of 9 publicly available databases: 7 image (with a total of 3832 distorted images with diverse distortions) and 2 video databases (totally 228 distorted videos). These show that the proposed method is overall better than several of the existing fullreference (FR) algorithms and two RR algorithms. Additionally, there is a graceful degradation in prediction performance as the amount of reference image information is reduced thereby confirming its scalability prospects. To enable comparisons and future study, a Matlab implementation of the proposed algorithm is available at http://www.ntu.edu.sg/home/wslin/reduced_phase.rar.

  16. Image-based spectroscopy for environmental monitoring

    Science.gov (United States)

    Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

    2014-03-01

    An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

  17. Fluorescence based molecular in vivo imaging

    International Nuclear Information System (INIS)

    Ebert, Bernd

    2008-01-01

    Molecular imaging represents a modern research area that allows the in vivo study of molecular biological process kinetics using appropriate probes and visualization methods. This methodology may be defined- apart from the contrast media injection - as non-abrasive. In order to reach an in vivo molecular process imaging as accurate as possible the effects of the used probes on the biological should not be too large. The contrast media as important part of the molecular imaging can significantly contribute to the understanding of molecular processes and to the development of tailored diagnostics and therapy. Since more than 15 years PTB is developing optic imaging systems that may be used for fluorescence based visualization of tissue phantoms, small animal models and the localization of tumors and their predecessors, and for the early recognition of inflammatory processes in clinical trials. Cellular changes occur during many diseases, thus the molecular imaging might be of importance for the early diagnosis of chronic inflammatory diseases. Fluorescent dyes can be used as unspecific or also as specific contrast media, which allow enhanced detection sensitivity

  18. Web Based Distributed Coastal Image Analysis System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This project develops Web based distributed image analysis system processing the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide decision...

  19. Canny edge-based deformable image registration.

    Science.gov (United States)

    Kearney, Vasant; Huang, Yihui; Mao, Weihua; Yuan, Baohong; Tang, Liping

    2017-02-07

    This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

  20. Illumination compensation in ground based hyperspectral imaging

    Science.gov (United States)

    Wendel, Alexander; Underwood, James

    2017-07-01

    Hyperspectral imaging has emerged as an important tool for analysing vegetation data in agricultural applications. Recently, low altitude and ground based hyperspectral imaging solutions have come to the fore, providing very high resolution data for mapping and studying large areas of crops in detail. However, these platforms introduce a unique set of challenges that need to be overcome to ensure consistent, accurate and timely acquisition of data. One particular problem is dealing with changes in environmental illumination while operating with natural light under cloud cover, which can have considerable effects on spectral shape. In the past this has been commonly achieved by imaging known reference targets at the time of data acquisition, direct measurement of irradiance, or atmospheric modelling. While capturing a reference panel continuously or very frequently allows accurate compensation for illumination changes, this is often not practical with ground based platforms, and impossible in aerial applications. This paper examines the use of an autonomous unmanned ground vehicle (UGV) to gather high resolution hyperspectral imaging data of crops under natural illumination. A process of illumination compensation is performed to extract the inherent reflectance properties of the crops, despite variable illumination. This work adapts a previously developed subspace model approach to reflectance and illumination recovery. Though tested on a ground vehicle in this paper, it is applicable to low altitude unmanned aerial hyperspectral imagery also. The method uses occasional observations of reference panel training data from within the same or other datasets, which enables a practical field protocol that minimises in-field manual labour. This paper tests the new approach, comparing it against traditional methods. Several illumination compensation protocols for high volume ground based data collection are presented based on the results. The findings in this paper are

  1. Imaging of skull base: Pictorial essay

    International Nuclear Information System (INIS)

    Raut, Abhijit A; Naphade, Prashant S; Chawla, Ashish

    2012-01-01

    The skull base anatomy is complex. Numerous vital neurovascular structures pass through multiple channels and foramina located in the base skull. With the advent of computerized tomography (CT) and magnetic resonance imaging (MRI), accurate preoperative lesion localization and evaluation of its relationship with adjacent neurovascular structures is possible. It is imperative that the radiologist and skull base surgeons are familiar with this complex anatomy for localizing the skull base lesion, reaching appropriate differential diagnosis, and deciding the optimal surgical approach. CT and MRI are complementary to each other and are often used together for the demonstration of the full disease extent. This article focuses on the radiological anatomy of the skull base and discusses few of the common pathologies affecting the skull base

  2. ImageSURF: An ImageJ Plugin for Batch Pixel-Based Image Segmentation Using Random Forests

    Directory of Open Access Journals (Sweden)

    Aidan O'Mara

    2017-11-01

    Full Text Available Image segmentation is a necessary step in automated quantitative imaging. ImageSURF is a macro-compatible ImageJ2/FIJI plugin for pixel-based image segmentation that considers a range of image derivatives to train pixel classifiers which are then applied to image sets of any size to produce segmentations without bias in a consistent, transparent and reproducible manner. The plugin is available from ImageJ update site http://sites.imagej.net/ImageSURF/ and source code from https://github.com/omaraa/ImageSURF. Funding statement: This research was supported by an Australian Government Research Training Program Scholarship.

  3. Monocular Depth Perception and Robotic Grasping of Novel Objects

    Science.gov (United States)

    2009-06-01

    obtain its full 3D shape, and applies even to textureless, translucent or reflective objects on which standard stereo 3D reconstruction fares poorly. We...purple) in image A. 3.3.4 Phantom planes This cue enforces occlusion constraints across multiple cameras. Concretely , each small plane (superpixel...needing to obtain its full 3D shape, and applies even to textureless, translucent or reflective objects on which standard stereo 3D reconstruction

  4. A hash-based image encryption algorithm

    Science.gov (United States)

    Cheddad, Abbas; Condell, Joan; Curran, Kevin; McKevitt, Paul

    2010-03-01

    There exist several algorithms that deal with text encryption. However, there has been little research carried out to date on encrypting digital images or video files. This paper describes a novel way of encrypting digital images with password protection using 1D SHA-2 algorithm coupled with a compound forward transform. A spatial mask is generated from the frequency domain by taking advantage of the conjugate symmetry of the complex imagery part of the Fourier Transform. This mask is then XORed with the bit stream of the original image. Exclusive OR (XOR), a logical symmetric operation, that yields 0 if both binary pixels are zeros or if both are ones and 1 otherwise. This can be verified simply by modulus (pixel1, pixel2, 2). Finally, confusion is applied based on the displacement of the cipher's pixels in accordance with a reference mask. Both security and performance aspects of the proposed method are analyzed, which prove that the method is efficient and secure from a cryptographic point of view. One of the merits of such an algorithm is to force a continuous tone payload, a steganographic term, to map onto a balanced bits distribution sequence. This bit balance is needed in certain applications, such as steganography and watermarking, since it is likely to have a balanced perceptibility effect on the cover image when embedding.

  5. Unsupervised image matching based on manifold alignment.

    Science.gov (United States)

    Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

    2012-08-01

    This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

  6. Toward CMOS image sensor based glucose monitoring.

    Science.gov (United States)

    Devadhasan, Jasmine Pramila; Kim, Sanghyo

    2012-09-07

    Complementary metal oxide semiconductor (CMOS) image sensor is a powerful tool for biosensing applications. In this present study, CMOS image sensor has been exploited for detecting glucose levels by simple photon count variation with high sensitivity. Various concentrations of glucose (100 mg dL(-1) to 1000 mg dL(-1)) were added onto a simple poly-dimethylsiloxane (PDMS) chip and the oxidation of glucose was catalyzed with the aid of an enzymatic reaction. Oxidized glucose produces a brown color with the help of chromogen during enzymatic reaction and the color density varies with the glucose concentration. Photons pass through the PDMS chip with varying color density and hit the sensor surface. Photon count was recognized by CMOS image sensor depending on the color density with respect to the glucose concentration and it was converted into digital form. By correlating the obtained digital results with glucose concentration it is possible to measure a wide range of blood glucose levels with great linearity based on CMOS image sensor and therefore this technique will promote a convenient point-of-care diagnosis.

  7. BEE FORAGE MAPPING BASED ON MULTISPECTRAL IMAGES LANDSAT

    Directory of Open Access Journals (Sweden)

    A. Moskalenko

    2016-10-01

    Full Text Available Possibilities of bee forage identification and mapping based on multispectral images have been shown in the research. Spectral brightness of bee forage has been determined with the use of satellite images. The effectiveness of some methods of image classification for mapping of bee forage is shown. Keywords: bee forage, mapping, multispectral images, image classification.

  8. Normative monocular visual acuity for early treatment diabetic retinopathy study charts in emmetropic children 5 to 12 years of age.

    Science.gov (United States)

    Dobson, Velma; Clifford-Donaldson, Candice E; Green, Tina K; Miller, Joseph M; Harvey, Erin M

    2009-07-01

    To provide normative data for children tested with Early Treatment Diabetic Retinopathy Study (ETDRS) charts. Cross-sectional study. A total of 252 Native American (Tohono O'odham) children aged 5 to 12 years. On the basis of cycloplegic refraction conducted on the day of testing, all were emmetropic (myopia < or =0.25 diopter [D] spherical equivalent, hyperopia < or =1.00 D spherical equivalent, and astigmatism < or =0.50 D in both eyes). Monocular visual acuity was tested at 4 m, using 1 ETDRS chart for the right eye (RE) and another for the left eye (LE). Visual acuity was scored as the total number of letters correctly identified, by naming or matching to letters on a lap card, and as the smallest letter size for which the child identified 3 of 5 letters correctly. Visual acuity results did not differ for the RE versus the LE, so data are reported for the RE only. Mean visual acuity for 5-year-olds (0.16 logarithm of the minimum angle of resolution [logMAR] [20/29]) was significantly worse than for 8-, 9-, 10-, 11-, and 12-year-olds (0.05 logMAR [20/22] or better at each age). The lower 95% prediction limit for determining whether a child has visual acuity within the normal range was 0.38 (20/48) for 5-year-olds and 0.30 (20/40) for 6- to 12-year-olds, which was reduced to 0.32 (20/42) for 5-year-olds and 0.21 (20/32) for 6- to 12-year-olds when recalculated with outlying data points removed. Mean interocular acuity difference did not vary by age, averaging less than 1 logMAR line at each age, with a lower 95% prediction limit of 0.17 log unit (1.7 logMAR lines) across all ages. For monocular visual acuity based on ETDRS charts to be in the normal range, it must be better than 20/50 for 5-year-olds and better than 20/40 for 6- to 12-year-olds. Normal interocular acuity difference includes values of less than 2 logMAR lines. Normative ETDRS visual acuity values are not as good as norms reported for adults, suggesting that a child's visual acuity results should

  9. Image superresolution of cytology images using wavelet based patch search

    Science.gov (United States)

    Vargas, Carlos; García-Arteaga, Juan D.; Romero, Eduardo

    2015-01-01

    Telecytology is a new research area that holds the potential of significantly reducing the number of deaths due to cervical cancer in developing countries. This work presents a novel super-resolution technique that couples high and low frequency information in order to reduce the bandwidth consumption of cervical image transmission. The proposed approach starts by decomposing into wavelets the high resolution images and transmitting only the lower frequency coefficients. The transmitted coefficients are used to reconstruct an image of the original size. Additional details are added by iteratively replacing patches of the wavelet reconstructed image with equivalent high resolution patches from a previously acquired image database. Finally, the original transmitted low frequency coefficients are used to correct the final image. Results show a higher signal to noise ratio in the proposed method over simply discarding high frequency wavelet coefficients or replacing directly down-sampled patches from the image-database.

  10. Cirurgia monocular para esotropias de grande ângulo: um novo paradigma Monocular surgery for large-angle esotropias: a new paradigm

    Directory of Open Access Journals (Sweden)

    Edmilson Gigante

    2009-02-01

    Full Text Available OBJETIVO: Demonstrar a viabilidade da cirurgia monocular no tratamento das esotropias de grande ângulo, praticando-se amplos recuos do reto medial (6 a 10 mm e grandes ressecções do reto lateral (8 a 10 mm. MÉTODOS: Foram operados, com anestesia geral e sem reajustes per ou pósoperatórios, 46 pacientes com esotropias de 50δ ou mais, relativamente comitantes. Os métodos utilizados para refratometria, medida da acuidade visual e do ângulo de desvio, foram os, tradicionalmente, utilizados em estrabologia. No pós-operatório, além das medidas na posição primária do olhar, foi feita uma avaliação da motilidade do olho operado, em adução e em abdução. RESULTADOS: Foram considerados quatro grupos de estudo, correspondendo a quatro períodos de tempo: uma semana, seis meses, dois anos e quatro a sete anos. Os resultados para o ângulo de desvio pós-cirúrgico foram compatíveis com os da literatura em geral e mantiveram-se estáveis ao longo do tempo. A motilidade do olho operado apresentou pequena limitação em adução e nenhuma em abdução, contrariando o encontrado na literatura estrabológica. Comparando os resultados de adultos com os de crianças e de amblíopes com não amblíopes, não foram encontradas diferenças estatisticamente significativas entre eles. CONCLUSÃO:Em face dos resultados encontrados, entende-se ser possível afirmar que a cirurgia monocular de recuo-ressecção pode ser considerada opção viável para o tratamento das esotropias de grande ângulo, tanto para adultos quanto para crianças, bem como para amblíopes e não amblíopes.PURPOSE: To demonstrate the feasibility of monocular surgery in the treatment of large-angle esotropias through large recessions of the medial rectus (6 to 10 mm and large resections of the lateral rectus (8 to 10 mm. METHODS: 46 patients were submitted to surgery. They had esotropias of 50Δor more that were relatively comitant. The patients were operated under general

  11. Compressive sensing based ptychography image encryption

    Science.gov (United States)

    Rawat, Nitin

    2015-09-01

    A compressive sensing (CS) based ptychography combined with an optical image encryption is proposed. The diffraction pattern is recorded through ptychography technique further compressed by non-uniform sampling via CS framework. The system requires much less encrypted data and provides high security. The diffraction pattern as well as the lesser measurements of the encrypted samples serves as a secret key which make the intruder attacks more difficult. Furthermore, CS shows that the linearly projected few random samples have adequate information for decryption with a dramatic volume reduction. Experimental results validate the feasibility and effectiveness of our proposed technique compared with the existing techniques. The retrieved images do not reveal any information with the original information. In addition, the proposed system can be robust even with partial encryption and under brute-force attacks.

  12. SQL based cardiovascular ultrasound image classification.

    Science.gov (United States)

    Nandagopalan, S; Suryanarayana, Adiga B; Sudarshan, T S B; Chandrashekar, Dhanalakshmi; Manjunath, C N

    2013-01-01

    This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables (NBCD) with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables (NBCC) using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.

  13. Accelerated Compressed Sensing Based CT Image Reconstruction.

    Science.gov (United States)

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  14. Accelerated Compressed Sensing Based CT Image Reconstruction

    Directory of Open Access Journals (Sweden)

    SayedMasoud Hashemi

    2015-01-01

    Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  15. Imaging of the central skull base.

    Science.gov (United States)

    Borges, Alexandra

    2009-11-01

    The central skull base (CSB) constitutes a frontier between the extracranial head and neck and the middle cranial fossa. The anatomy of this region is complex, containing most of the bony foramina and canals of the skull base traversed by several neurovascular structures that can act as routes of spread for pathologic processes. Lesions affecting the CSB can be intrinsic to its bony-cartilaginous components; can arise from above, within the intracranial compartment; or can arise from below, within the extracranial head and neck. Crosssectional imaging is indispensable in the diagnosis, treatment planning, and follow-up of patients with CSB lesions. This review focuses on a systematic approach to this region based on an anatomic division that takes into account the major tissue constituents of the CSB.

  16. OCML-based colour image encryption

    International Nuclear Information System (INIS)

    Rhouma, Rhouma; Meherzi, Soumaya; Belghith, Safya

    2009-01-01

    The chaos-based cryptographic algorithms have suggested some new ways to develop efficient image-encryption schemes. While most of these schemes are based on low-dimensional chaotic maps, it has been proposed recently to use high-dimensional chaos namely spatiotemporal chaos, which is modelled by one-way coupled-map lattices (OCML). Owing to their hyperchaotic behaviour, such systems are assumed to enhance the cryptosystem security. In this paper, we propose an OCML-based colour image encryption scheme with a stream cipher structure. We use a 192-bit-long external key to generate the initial conditions and the parameters of the OCML. We have made several tests to check the security of the proposed cryptosystem namely, statistical tests including histogram analysis, calculus of the correlation coefficients of adjacent pixels, security test against differential attack including calculus of the number of pixel change rate (NPCR) and unified average changing intensity (UACI), and entropy calculus. The cryptosystem speed is analyzed and tested as well.

  17. HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter

    Directory of Open Access Journals (Sweden)

    Qingjiao Sun

    2016-01-01

    Full Text Available Pathological image enhancement is a significant topic in the field of pathological image processing. This paper proposes a high dynamic range (HDR pathological image enhancement method based on improved bias field correction and guided image filter (GIF. Firstly, a preprocessing including stain normalization and wavelet denoising is performed for Haematoxylin and Eosin (H and E stained pathological image. Then, an improved bias field correction model is developed to enhance the influence of light for high-frequency part in image and correct the intensity inhomogeneity and detail discontinuity of image. Next, HDR pathological image is generated based on least square method using low dynamic range (LDR image, H and E channel images. Finally, the fine enhanced image is acquired after the detail enhancement process. Experiments with 140 pathological images demonstrate the performance advantages of our proposed method as compared with related work.

  18. Image-Based Models Using Crowdsourcing Strategy

    Directory of Open Access Journals (Sweden)

    Antonia Spanò

    2016-12-01

    Full Text Available The conservation and valorization of Cultural Heritage require an extensive documentation, both in properly historic-artistic terms and regarding the physical characteristics of position, shape, color, and geometry. With the use of digital photogrammetry that make acquisition of overlapping images for 3D photo modeling and with the development of dense and accurate 3D point models, it is possible to obtain high-resolution orthoprojections of surfaces.Recent years have seen a growing interest in crowdsourcing that holds in the field of the protection and dissemination of cultural heritage, in parallel there is an increasing awareness for contributing the generation of digital models with the immense wealth of images available on the web which are useful for documentation heritage.In this way, the availability and ease the automation of SfM (Structure from Motion algorithm enables the generation of digital models of the built heritage, which can be inserted positively in crowdsourcing processes. In fact, non-expert users can handle the technology in the process of acquisition, which today is one of the fundamental points to involve the wider public to the cultural heritage protection. To present the image based models and their derivatives that can be made from a great digital resource; the current approach is useful for the little-known heritage or not easily accessible buildings as an emblematic case study that was selected. It is the Vank Cathedral in Isfahan in Iran: the availability of accurate point clouds and reliable orthophotos are very convenient since the building of the Safavid epoch (cent. XVII-XVIII completely frescoed with the internal surfaces, which the architecture and especially the architectural decoration reach their peak.The experimental part of the paper explores also some aspects of usability of the digital output from the image based modeling methods. The availability of orthophotos allows and facilitates the iconographic

  19. Object localization in handheld thermal images for fireground understanding

    Science.gov (United States)

    Vandecasteele, Florian; Merci, Bart; Jalalvand, Azarakhsh; Verstockt, Steven

    2017-05-01

    Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

  20. Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

    Science.gov (United States)

    Liu, Min; Wang, Xueping; Zhang, Hongzhong

    2018-03-01

    In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Delayed Monocular SLAM Approach Applied to Unmanned Aerial Vehicles.

    Science.gov (United States)

    Munguia, Rodrigo; Urzua, Sarquis; Grau, Antoni

    2016-01-01

    In recent years, many researchers have addressed the issue of making Unmanned Aerial Vehicles (UAVs) more and more autonomous. In this context, the state estimation of the vehicle position is a fundamental necessity for any application involving autonomy. However, the problem of position estimation could not be solved in some scenarios, even when a GPS signal is available, for instance, an application requiring performing precision manoeuvres in a complex environment. Therefore, some additional sensory information should be integrated into the system in order to improve accuracy and robustness. In this work, a novel vision-based simultaneous localization and mapping (SLAM) method with application to unmanned aerial vehicles is proposed. One of the contributions of this work is to design and develop a novel technique for estimating features depth which is based on a stochastic technique of triangulation. In the proposed method the camera is mounted over a servo-controlled gimbal that counteracts the changes in attitude of the quadcopter. Due to the above assumption, the overall problem is simplified and it is focused on the position estimation of the aerial vehicle. Also, the tracking process of visual features is made easier due to the stabilized video. Another contribution of this work is to demonstrate that the integration of very noisy GPS measurements into the system for an initial short period of time is enough to initialize the metric scale. The performance of this proposed method is validated by means of experiments with real data carried out in unstructured outdoor environments. A comparative study shows that, when compared with related methods, the proposed approach performs better in terms of accuracy and computational time.

  2. Delayed Monocular SLAM Approach Applied to Unmanned Aerial Vehicles.

    Directory of Open Access Journals (Sweden)

    Rodrigo Munguia

    Full Text Available In recent years, many researchers have addressed the issue of making Unmanned Aerial Vehicles (UAVs more and more autonomous. In this context, the state estimation of the vehicle position is a fundamental necessity for any application involving autonomy. However, the problem of position estimation could not be solved in some scenarios, even when a GPS signal is available, for instance, an application requiring performing precision manoeuvres in a complex environment. Therefore, some additional sensory information should be integrated into the system in order to improve accuracy and robustness. In this work, a novel vision-based simultaneous localization and mapping (SLAM method with application to unmanned aerial vehicles is proposed. One of the contributions of this work is to design and develop a novel technique for estimating features depth which is based on a stochastic technique of triangulation. In the proposed method the camera is mounted over a servo-controlled gimbal that counteracts the changes in attitude of the quadcopter. Due to the above assumption, the overall problem is simplified and it is focused on the position estimation of the aerial vehicle. Also, the tracking process of visual features is made easier due to the stabilized video. Another contribution of this work is to demonstrate that the integration of very noisy GPS measurements into the system for an initial short period of time is enough to initialize the metric scale. The performance of this proposed method is validated by means of experiments with real data carried out in unstructured outdoor environments. A comparative study shows that, when compared with related methods, the proposed approach performs better in terms of accuracy and computational time.

  3. Automated image based prominent nucleoli detection.

    Science.gov (United States)

    Yap, Choon K; Kalaw, Emarene M; Singh, Malay; Chong, Kian T; Giron, Danilo M; Huang, Chao-Hui; Cheng, Li; Law, Yan N; Lee, Hwee Kuan

    2015-01-01

    Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

  4. Automated image based prominent nucleoli detection

    Directory of Open Access Journals (Sweden)

    Choon K Yap

    2015-01-01

    Full Text Available Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

  5. The Calibration Home Base for Imaging Spectrometers

    Directory of Open Access Journals (Sweden)

    Johannes Felix Simon Brachmann

    2016-08-01

    Full Text Available The Calibration Home Base (CHB is an optical laboratory designed for the calibration of imaging spectrometers for the VNIR/SWIR wavelength range. Radiometric, spectral and geometric calibration as well as the characterization of sensor signal dependency on polarization are realized in a precise and highly automated fashion. This allows to carry out a wide range of time consuming measurements in an ecient way. The implementation of ISO 9001 standards in all procedures ensures a traceable quality of results. Spectral measurements in the wavelength range 380–1000 nm are performed to a wavelength uncertainty of +- 0.1 nm, while an uncertainty of +-0.2 nm is reached in the wavelength range 1000 – 2500 nm. Geometric measurements are performed at increments of 1.7 µrad across track and 7.6 µrad along track. Radiometric measurements reach an absolute uncertainty of +-3% (k=1. Sensor artifacts, such as caused by stray light will be characterizable and correctable in the near future. For now, the CHB is suitable for the characterization of pushbroom sensors, spectrometers and cameras. However, it is planned to extend the CHBs capabilities in the near future such that snapshot hyperspectral imagers can be characterized as well. The calibration services of the CHB are open to third party customers from research institutes as well as industry.

  6. Monocular tool control, eye dominance, and laterality in New Caledonian crows.

    Science.gov (United States)

    Martinho, Antone; Burns, Zackory T; von Bayern, Auguste M P; Kacelnik, Alex

    2014-12-15

    Tool use, though rare, is taxonomically widespread, but morphological adaptations for tool use are virtually unknown. We focus on the New Caledonian crow (NCC, Corvus moneduloides), which displays some of the most innovative tool-related behavior among nonhumans. One of their major food sources is larvae extracted from burrows with sticks held diagonally in the bill, oriented with individual, but not species-wide, laterality. Among possible behavioral and anatomical adaptations for tool use, NCCs possess unusually wide binocular visual fields (up to 60°), suggesting that extreme binocular vision may facilitate tool use. Here, we establish that during natural extractions, tool tips can only be viewed by the contralateral eye. Thus, maintaining binocular view of tool tips is unlikely to have selected for wide binocular fields; the selective factor is more likely to have been to allow each eye to see far enough across the midsagittal line to view the tool's tip monocularly. Consequently, we tested the hypothesis that tool side preference follows eye preference and found that eye dominance does predict tool laterality across individuals. This contrasts with humans' species-wide motor laterality and uncorrelated motor-visual laterality, possibly because bill-held tools are viewed monocularly and move in concert with eyes, whereas hand-held tools are visible to both eyes and allow independent combinations of eye preference and handedness. This difference may affect other models of coordination between vision and mechanical control, not necessarily involving tools. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

    Science.gov (United States)

    Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

    2014-01-01

    This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

  8. An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment

    Directory of Open Access Journals (Sweden)

    Deshi Li

    2016-01-01

    Full Text Available Range estimation is crucial for maintaining a safe distance, in particular for vision navigation and localization. Monocular autonomous vehicles are appropriate for outdoor environment due to their mobility and operability. However, accurate range estimation using vision system is challenging because of the nonholonomic dynamics and susceptibility of vehicles. In this paper, a measuring rectification algorithm for range estimation under shaking conditions is designed. The proposed method focuses on how to estimate range using monocular vision when a shake occurs and the algorithm only requires the pose variations of the camera to be acquired. Simultaneously, it solves the problem of how to assimilate results from different kinds of sensors. To eliminate measuring errors by shakes, we establish a pose-range variation model. Afterwards, the algebraic relation between distance increment and a camera’s poses variation is formulated. The pose variations are presented in the form of roll, pitch, and yaw angle changes to evaluate the pixel coordinate incensement. To demonstrate the superiority of our proposed algorithm, the approach is validated in a laboratory environment using Pioneer 3-DX robots. The experimental results demonstrate that the proposed approach improves in the range accuracy significantly.

  9. Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

    Directory of Open Access Journals (Sweden)

    Yanhua Jiang

    2014-09-01

    Full Text Available This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments.

  10. Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

    Science.gov (United States)

    Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

    2012-08-01

    This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

  11. Mobile object retrieval in server-based image databases

    Science.gov (United States)

    Manger, D.; Pagel, F.; Widak, H.

    2013-05-01

    The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

  12. Image based book cover recognition and retrieval

    Science.gov (United States)

    Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

    2017-11-01

    In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

  13. Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    Praveen Agarwal

    2017-06-01

    Full Text Available Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.

  14. Image-based reflectance conversion of ASTER and IKONOS ...

    African Journals Online (AJOL)

    Spectral signatures derived from different image-based models for ASTER and IKONOS were inspected visually as first departure. This was followed by comparison of the total accuracy and Kappa index computed from supervised classification of images that were derived from different image-based atmospheric correction ...

  15. Chaos-based image encryption algorithm

    International Nuclear Information System (INIS)

    Guan Zhihong; Huang Fangjun; Guan Wenjie

    2005-01-01

    In this Letter, a new image encryption scheme is presented, in which shuffling the positions and changing the grey values of image pixels are combined to confuse the relationship between the cipher-image and the plain-image. Firstly, the Arnold cat map is used to shuffle the positions of the image pixels in the spatial-domain. Then the discrete output signal of the Chen's chaotic system is preprocessed to be suitable for the grayscale image encryption, and the shuffled image is encrypted by the preprocessed signal pixel by pixel. The experimental results demonstrate that the key space is large enough to resist the brute-force attack and the distribution of grey values of the encrypted image has a random-like behavior

  16. A fractal-based image encryption system

    KAUST Repository

    Abd-El-Hafiz, S. K.; Radwan, Ahmed Gomaa; Abdel Haleem, Sherif H.; Barakat, Mohamed L.

    2014-01-01

    single-fractal image and statistical analysis is performed. A general encryption system utilising multiple fractal images is, then, introduced to improve the performance and increase the encryption key up to hundreds of bits. This improvement is achieved

  17. Multi region based image retrieval system

    Indian Academy of Sciences (India)

    data mining, information theory, statistics and psychology. ∗ .... ground complication and independent of image size and orientation (Zhang 2007). ..... Figure 2. Significant regions: (a) the input image, (b) the primary significant region, (c) the ...

  18. Machine learning based analysis of cardiovascular images

    NARCIS (Netherlands)

    Wolterink, JM

    2017-01-01

    Cardiovascular diseases (CVDs), including coronary artery disease (CAD) and congenital heart disease (CHD) are the global leading cause of death. Computed tomography (CT) and magnetic resonance imaging (MRI) allow non-invasive imaging of cardiovascular structures. This thesis presents machine

  19. Tissues segmentation based on multi spectral medical images

    Science.gov (United States)

    Li, Ya; Wang, Ying

    2017-11-01

    Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

  20. COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATION

    OpenAIRE

    Kanika Kapoor and Shaveta Arora

    2015-01-01

    Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi Histog...

  1. Location-based Services using Image Search

    DEFF Research Database (Denmark)

    Vertongen, Pieter-Paulus; Hansen, Dan Witzner

    2008-01-01

    Recent developments in image search has made them sufficiently efficient to be used in real-time applications. GPS has become a popular navigation tool. While GPS information provide reasonably good accuracy, they are not always present in all hand held devices nor are they accurate in all situat...... of the image search engine and database image location knowledge, the location is determined of the query image and associated data can be presented to the user....

  2. Hierarchical clustering of RGB surface water images based on MIA ...

    African Journals Online (AJOL)

    2009-11-25

    Nov 25, 2009 ... similar water-related images within a testing database of 126 RGB images. .... consequently treated by SVD-based PCA and the PCA outputs partitioned into .... green. Other colours, mostly brown and grey, dominate in.

  3. New LSB-based colour image steganography method to enhance ...

    Indian Academy of Sciences (India)

    Mustafa Cem kasapbaşi

    2018-04-27

    Apr 27, 2018 ... evaluate the proposed method, comparative performance tests are carried out against different spatial image ... image steganography applications based on LSB are ..... worst case scenario could occur when having highest.

  4. Quantum Image Steganography and Steganalysis Based On LSQu-Blocks Image Information Concealing Algorithm

    Science.gov (United States)

    A. AL-Salhi, Yahya E.; Lu, Songfeng

    2016-08-01

    Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.

  5. Image dissimilarity-based quantification of lung disease from CT

    DEFF Research Database (Denmark)

    Sørensen, Lauge; Loog, Marco; Lo, Pechin

    2010-01-01

    In this paper, we propose to classify medical images using dissimilarities computed between collections of regions of interest. The images are mapped into a dissimilarity space using an image dissimilarity measure, and a standard vector space-based classifier is applied in this space. The classif......In this paper, we propose to classify medical images using dissimilarities computed between collections of regions of interest. The images are mapped into a dissimilarity space using an image dissimilarity measure, and a standard vector space-based classifier is applied in this space...

  6. Image-based corrosion recognition for ship steel structures

    Science.gov (United States)

    Ma, Yucong; Yang, Yang; Yao, Yuan; Li, Shengyuan; Zhao, Xuefeng

    2018-03-01

    Ship structures are subjected to corrosion inevitably in service. Existed image-based methods are influenced by the noises in images because they recognize corrosion by extracting features. In this paper, a novel method of image-based corrosion recognition for ship steel structures is proposed. The method utilizes convolutional neural networks (CNN) and will not be affected by noises in images. A CNN used to recognize corrosion was designed through fine-turning an existing CNN architecture and trained by datasets built using lots of images. Combining the trained CNN classifier with a sliding window technique, the corrosion zone in an image can be recognized.

  7. An Image Encryption Method Based on Bit Plane Hiding Technology

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; LI Zhitang; TU Hao

    2006-01-01

    A novel image hiding method based on the correlation analysis of bit plane is described in this paper. Firstly, based on the correlation analysis, different bit plane of a secret image is hided in different bit plane of several different open images. And then a new hiding image is acquired by a nesting "Exclusive-OR" operation on those images obtained from the first step. At last, by employing image fusion technique, the final hiding result is achieved. The experimental result shows that the method proposed in this paper is effective.

  8. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    Science.gov (United States)

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications.

  9. Parallel image encryption algorithm based on discretized chaotic map

    International Nuclear Information System (INIS)

    Zhou Qing; Wong Kwokwo; Liao Xiaofeng; Xiang Tao; Hu Yue

    2008-01-01

    Recently, a variety of chaos-based algorithms were proposed for image encryption. Nevertheless, none of them works efficiently in parallel computing environment. In this paper, we propose a framework for parallel image encryption. Based on this framework, a new algorithm is designed using the discretized Kolmogorov flow map. It fulfills all the requirements for a parallel image encryption algorithm. Moreover, it is secure and fast. These properties make it a good choice for image encryption on parallel computing platforms

  10. Gabor filter based fingerprint image enhancement

    Science.gov (United States)

    Wang, Jin-Xiang

    2013-03-01

    Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

  11. Image based radiotherapy, where we stand?

    International Nuclear Information System (INIS)

    Rangacharyulu, Chary

    2016-01-01

    Since the invention of X-ray tube, image based therapy has evolved in many ways. The latest tool is the MR-Linac, where MRI guided Linac Bremsstrahlung radiation therapy is being promoted to cure cancers. Studies are underway to combine proton radiation therapy with positron emission tomography. Also, there are ideas for Bremsstrahlung beam therapy using a few MeV photons to combine with real-time positron emission tomography. While these technologies offer promises to revolutionize radiation oncology, one should be concerned about the potential excessive doses and their consequences to the patient. Also, one should be wary about the instantaneous real-time responses from oncologist or, even a bit scarier, automated decisions based on algorithm dictated protocols, which may result in life and death or even worse, those which may adversely affect the well being of a patient. In essence, treatment protocols which incorporate a thorough, careful assessments are warranted. Further concerns are economics of these developments weighed against the quality of life to the patients and their beloved's. This talk will present the current status and speculate on the possible developments with a few cautionary remarks. (author)

  12. a Variant of Lsd-Slam Capable of Processing High-Speed Low-Framerate Monocular Datasets

    Science.gov (United States)

    Schmid, S.; Fritsch, D.

    2017-11-01

    We develop a new variant of LSD-SLAM, called C-LSD-SLAM, which is capable of performing monocular tracking and mapping in high-speed low-framerate situations such as those of the KITTI datasets. The methods used here are robust against the influence of erronously triangulated points near the epipolar direction, which otherwise causes tracking divergence.

  13. Charles Miller Fisher: the 65th anniversary of the publication of his groundbreaking study "Transient Monocular Blindness Associated with Hemiplegia".

    Science.gov (United States)

    Araújo, Tiago Fernando Souza de; Lange, Marcos; Zétola, Viviane H; Massaro, Ayrton; Teive, Hélio A G

    2017-10-01

    Charles Miller Fisher is considered the father of modern vascular neurology and one of the giants of neurology in the 20th century. This historical review emphasizes Prof. Fisher's magnificent contribution to vascular neurology and celebrates the 65th anniversary of the publication of his groundbreaking study, "Transient Monocular Blindness Associated with Hemiplegia."

  14. Image encryption based on permutation-substitution using chaotic map and Latin Square Image Cipher

    Science.gov (United States)

    Panduranga, H. T.; Naveen Kumar, S. K.; Kiran, HASH(0x22c8da0)

    2014-06-01

    In this paper we presented a image encryption based on permutation-substitution using chaotic map and Latin square image cipher. The proposed method consists of permutation and substitution process. In permutation process, plain image is permuted according to chaotic sequence generated using chaotic map. In substitution process, based on secrete key of 256 bit generate a Latin Square Image Cipher (LSIC) and this LSIC is used as key image and perform XOR operation between permuted image and key image. The proposed method can applied to any plain image with unequal width and height as well and also resist statistical attack, differential attack. Experiments carried out for different images of different sizes. The proposed method possesses large key space to resist brute force attack.

  15. A Novel Quantum Image Steganography Scheme Based on LSB

    Science.gov (United States)

    Zhou, Ri-Gui; Luo, Jia; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen

    2018-06-01

    Based on the NEQR representation of quantum images and least significant bit (LSB) scheme, a novel quantum image steganography scheme is proposed. The sizes of the cover image and the original information image are assumed to be 4 n × 4 n and n × n, respectively. Firstly, the bit-plane scrambling method is used to scramble the original information image. Then the scrambled information image is expanded to the same size of the cover image by using the key only known to the operator. The expanded image is scrambled to be a meaningless image with the Arnold scrambling. The embedding procedure and extracting procedure are carried out by K 1 and K 2 which are under control of the operator. For validation of the presented scheme, the peak-signal-to-noise ratio (PSNR), the capacity, the security of the images and the circuit complexity are analyzed.

  16. A new design for SLAM front-end based on recursive SOM

    Science.gov (United States)

    Yang, Xuesi; Xia, Shengping

    2015-12-01

    Aiming at the graph optimization-based monocular SLAM, a novel design for the front-end in single camera SLAM is proposed, based on the recursive SOM. Pixel intensities are directly used to achieve image registration and motion estimation, which can save time compared with the current appearance-based frameworks, usually including feature extraction and matching. Once a key-frame is identified, a recursive SOM is used to actualize loop-closure detecting, resulting a more precise location. The experiment on a public dataset validates our method on a computer with a quicker and effective result.

  17. Molecular–Genetic Imaging: A Nuclear Medicine–Based Perspective

    Directory of Open Access Journals (Sweden)

    Ronald G. Blasberg

    2002-07-01

    Full Text Available Molecular imaging is a relatively new discipline, which developed over the past decade, initially driven by in situ reporter imaging technology. Noninvasive in vivo molecular–genetic imaging developed more recently and is based on nuclear (positron emission tomography [PET], gamma camera, autoradiography imaging as well as magnetic resonance (MR and in vivo optical imaging. Molecular–genetic imaging has its roots in both molecular biology and cell biology, as well as in new imaging technologies. The focus of this presentation will be nuclear-based molecular–genetic imaging, but it will comment on the value and utility of combining different imaging modalities. Nuclear-based molecular imaging can be viewed in terms of three different imaging strategies: (1 “indirect” reporter gene imaging; (2 “direct” imaging of endogenous molecules; or (3 “surrogate” or “bio-marker” imaging. Examples of each imaging strategy will be presented and discussed. The rapid growth of in vivo molecular imaging is due to the established base of in vivo imaging technologies, the established programs in molecular and cell biology, and the convergence of these disciplines. The development of versatile and sensitive assays that do not require tissue samples will be of considerable value for monitoring molecular–genetic and cellular processes in animal models of human disease, as well as for studies in human subjects in the future. Noninvasive imaging of molecular–genetic and cellular processes will complement established ex vivo molecular–biological assays that require tissue sampling, and will provide a spatial as well as a temporal dimension to our understanding of various diseases and disease processes.

  18. Ghost imaging based on Pearson correlation coefficients

    International Nuclear Information System (INIS)

    Yu Wen-Kai; Yao Xu-Ri; Liu Xue-Feng; Li Long-Zhen; Zhai Guang-Jie

    2015-01-01

    Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. (paper)

  19. Improved Mesh_Based Image Morphing ‎

    Directory of Open Access Journals (Sweden)

    Mohammed Abdullah Taha

    2017-11-01

    Full Text Available Image morphing is a multi-step process that generates a sequence of transitions between two images. The thought is to get a ₔgrouping of middle pictures which, when ₔassembled with the first pictures would represent the change from one picture to the other.  The process of morphing requires time and attention to detail in order to get good results. Morphing image requires at least two processes warping and cross dissolve. Warping is the process of geometric transformation of images. The cross dissolve is the process interpolation of color of eachₔ pixel from the first image value to theₔ corresponding second imageₔ value over the time. Image morphing techniques differ from in the approach of image warping procedure. This work presents a survey of different techniques to construct morphing images by review the different warping techniques. One of the predominant approaches of warping process is mesh warping which suffers from some problems including ghosting. This work proposed and implements an improved mesh warping technique to construct morphing images. The results show that the proposed approach can overcome the problems of the traditional mesh technique

  20. Image fusion between whole body FDG PET images and whole body MRI images using a full-automatic mutual information-based multimodality image registration software

    International Nuclear Information System (INIS)

    Uchida, Yoshitaka; Nakano, Yoshitada; Fujibuchi, Toshiou; Isobe, Tomoko; Kazama, Toshiki; Ito, Hisao

    2006-01-01

    We attempted image fusion between whole body PET and whole body MRI of thirty patients using a full-automatic mutual information (MI) -based multimodality image registration software and evaluated accuracy of this method and impact of the coregistrated imaging on diagnostic accuracy. For 25 of 30 fused images in body area, translating gaps were within 6 mm in all axes and rotating gaps were within 2 degrees around all axes. In head and neck area, considerably much gaps caused by difference of head inclination at imaging occurred in 16 patients, however these gaps were able to decrease by fused separately. In 6 patients, diagnostic accuracy using PET/MRI fused images was superior compared by PET image alone. This work shows that whole body FDG PET images and whole body MRI images can be automatically fused using MI-based multimodality image registration software accurately and this technique can add useful information when evaluating FDG PET images. (author)

  1. Simple and robust image-based autofocusing for digital microscopy.

    Science.gov (United States)

    Yazdanfar, Siavash; Kenny, Kevin B; Tasimi, Krenar; Corwin, Alex D; Dixon, Elizabeth L; Filkins, Robert J

    2008-06-09

    A simple image-based autofocusing scheme for digital microscopy is demonstrated that uses as few as two intermediate images to bring the sample into focus. The algorithm is adapted to a commercial inverted microscope and used to automate brightfield and fluorescence imaging of histopathology tissue sections.

  2. Scene matching based on non-linear pre-processing on reference image and sensed image

    Institute of Scientific and Technical Information of China (English)

    Zhong Sheng; Zhang Tianxu; Sang Nong

    2005-01-01

    To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.

  3. Content Based Retrieval System for Magnetic Resonance Images

    International Nuclear Information System (INIS)

    Trojachanets, Katarina

    2010-01-01

    The amount of medical images is continuously increasing as a consequence of the constant growth and development of techniques for digital image acquisition. Manual annotation and description of each image is impractical, expensive and time consuming approach. Moreover, it is an imprecise and insufficient way for describing all information stored in medical images. This induces the necessity for developing efficient image storage, annotation and retrieval systems. Content based image retrieval (CBIR) emerges as an efficient approach for digital image retrieval from large databases. It includes two phases. In the first phase, the visual content of the image is analyzed and the feature extraction process is performed. An appropriate descriptor, namely, feature vector is then associated with each image. These descriptors are used in the second phase, i.e. the retrieval process. With the aim to improve the efficiency and precision of the content based image retrieval systems, feature extraction and automatic image annotation techniques are subject of continuous researches and development. Including the classification techniques in the retrieval process enables automatic image annotation in an existing CBIR system. It contributes to more efficient and easier image organization in the system.Applying content based retrieval in the field of magnetic resonance is a big challenge. Magnetic resonance imaging is an image based diagnostic technique which is widely used in medical environment. According to this, the number of magnetic resonance images is enormously growing. Magnetic resonance images provide plentiful medical information, high resolution and specific nature. Thus, the capability of CBIR systems for image retrieval from large database is of great importance for efficient analysis of this kind of images. The aim of this thesis is to propose content based retrieval system architecture for magnetic resonance images. To provide the system efficiency, feature

  4. A New Images Hiding Scheme Based on Chaotic Sequences

    Institute of Scientific and Technical Information of China (English)

    LIU Nian-sheng; GUO Dong-hui; WU Bo-xi; Parr G

    2005-01-01

    We propose a data hidding technique in a still image. This technique is based on chaotic sequence in the transform domain of covert image. We use different chaotic random sequences multiplied by multiple sensitive images, respectively, to spread the spectrum of sensitive images. Multiple sensitive images are hidden in a covert image as a form of noise. The results of theoretical analysis and computer simulation show the new hiding technique have better properties with high security, imperceptibility and capacity for hidden information in comparison with the conventional scheme such as LSB (Least Significance Bit).

  5. Fibre laser based broadband THz imaging systems

    DEFF Research Database (Denmark)

    Eichhorn, Finn

    imaging techniques. This thesis exhibits that fiber technology can improve the robustness and the flexibility of terahertz imaging systems both by the use of fiber-optic light sources and the employment of optical fibers as light distribution medium. The main focus is placed on multi-element terahertz...

  6. FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Zhao

    2017-09-01

    Full Text Available The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

  7. Real-Time Algorithm for Relative Position Estimation Between Person and Robot Using a Monocular Camera

    International Nuclear Information System (INIS)

    Lee, Jung Uk; Sun, Ju Young; Won, Mooncheol

    2013-01-01

    In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner

  8. A method of real-time detection for distant moving obstacles by monocular vision

    Science.gov (United States)

    Jia, Bao-zhi; Zhu, Ming

    2013-12-01

    In this paper, we propose an approach for detection of distant moving obstacles like cars and bicycles by a monocular camera to cooperate with ultrasonic sensors in low-cost condition. We are aiming at detecting distant obstacles that move toward our autonomous navigation car in order to give alarm and keep away from them. Method of frame differencing is applied to find obstacles after compensation of camera's ego-motion. Meanwhile, each obstacle is separated from others in an independent area and given a confidence level to indicate whether it is coming closer. The results on an open dataset and our own autonomous navigation car have proved that the method is effective for detection of distant moving obstacles in real-time.

  9. Real-Time Algorithm for Relative Position Estimation Between Person and Robot Using a Monocular Camera

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung Uk [Samsung Electroics, Suwon (Korea, Republic of); Sun, Ju Young; Won, Mooncheol [Chungnam Nat' l Univ., Daejeon (Korea, Republic of)

    2013-12-15

    In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner.

  10. A new hyperspectral image compression paradigm based on fusion

    Science.gov (United States)

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

    2016-10-01

    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  11. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  12. Fingerprint Image Enhancement Based on Second Directional Derivative of the Digital Image

    Directory of Open Access Journals (Sweden)

    Onnia Vesa

    2002-01-01

    Full Text Available This paper presents a novel approach of fingerprint image enhancement that relies on detecting the fingerprint ridges as image regions where the second directional derivative of the digital image is positive. A facet model is used in order to approximate the derivatives at each image pixel based on the intensity values of pixels located in a certain neighborhood. We note that the size of this neighborhood has a critical role in achieving accurate enhancement results. Using neighborhoods of various sizes, the proposed algorithm determines several candidate binary representations of the input fingerprint pattern. Subsequently, an output binary ridge-map image is created by selecting image zones, from the available binary image candidates, according to a MAP selection rule. Two public domain collections of fingerprint images are used in order to objectively assess the performance of the proposed fingerprint image enhancement approach.

  13. Developing students’ ideas about lens imaging: teaching experiments with an image-based approach

    Science.gov (United States)

    Grusche, Sascha

    2017-07-01

    Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists’ analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students’ ideas, teaching experiments are performed and evaluated using qualitative content analysis. Some of the students’ ideas have not been reported before, namely those related to blurry lens images, and those developed by the proposed teaching approach. To describe learning pathways systematically, a conception-versus-time coordinate system is introduced, specifying how teaching actions help students advance toward a scientific understanding.

  14. COMPARISON AND EVALUATION OF CLUSTER BASED IMAGE SEGMENTATION TECHNIQUES

    OpenAIRE

    Hetangi D. Mehta*, Daxa Vekariya, Pratixa Badelia

    2017-01-01

    Image segmentation is the classification of an image into different groups. Numerous algorithms using different approaches have been proposed for image segmentation. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different...

  15. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  16. New calibration technique for KCD-based megavoltage imaging

    Science.gov (United States)

    Samant, Sanjiv S.; Zheng, Wei; DiBianca, Frank A.; Zeman, Herbert D.; Laughter, Joseph S.

    1999-05-01

    In megavoltage imaging, current commercial electronic portal imaging devices (EPIDs), despite having the advantage of immediate digital imaging over film, suffer from poor image contrast and spatial resolution. The feasibility of using a kinestatic charge detector (KCD) as an EPID to provide superior image contrast and spatial resolution for portal imaging has already been demonstrated in a previous paper. The KCD system had the additional advantage of requiring an extremely low dose per acquired image, allowing for superior imaging to be reconstructed form a single linac pulse per image pixel. The KCD based images utilized a dose of two orders of magnitude less that for EPIDs and film. Compared with the current commercial EPIDs and film, the prototype KCD system exhibited promising image qualities, despite being handicapped by the use of a relatively simple image calibration technique, and the performance limits of medical linacs on the maximum linac pulse frequency and energy flux per pulse delivered. This image calibration technique fixed relative image pixel values based on a linear interpolation of extrema provided by an air-water calibration, and accounted only for channel-to-channel variations. The counterpart of this for area detectors is the standard flat fielding method. A comprehensive calibration protocol has been developed. The new technique additionally corrects for geometric distortions due to variations in the scan velocity, and timing artifacts caused by mis-synchronization between the linear accelerator and the data acquisition system (DAS). The role of variations in energy flux (2 - 3%) on imaging is demonstrated to be not significant for the images considered. The methodology is presented, and the results are discussed for simulated images. It also allows for significant improvements in the signal-to- noise ratio (SNR) by increasing the dose using multiple images without having to increase the linac pulse frequency or energy flux per pulse. The

  17. Chromaticity based smoke removal in endoscopic images

    Science.gov (United States)

    Tchaka, Kevin; Pawar, Vijay M.; Stoyanov, Danail

    2017-02-01

    In minimally invasive surgery, image quality is a critical pre-requisite to ensure a surgeons ability to perform a procedure. In endoscopic procedures, image quality can deteriorate for a number of reasons such as fogging due to the temperature gradient after intra-corporeal insertion, lack of focus and due to smoke generated when using electro-cautery to dissect tissues without bleeding. In this paper we investigate the use of vision processing techniques to remove surgical smoke and improve the clarity of the image. We model the image formation process by introducing a haze medium to account for the degradation of visibility. For simplicity and computational efficiency we use an adapted dark-channel prior method combined with histogram equalization to remove smoke artifacts to recover the radiance image and enhance the contrast and brightness of the final result. Our initial results on images from robotic assisted procedures are promising and show that the proposed approach may be used to enhance image quality during surgery without additional suction devices. In addition, the processing pipeline may be used as an important part of a robust surgical vision pipeline that can continue working in the presence of smoke.

  18. Remote sensing image segmentation based on Hadoop cloud platform

    Science.gov (United States)

    Li, Jie; Zhu, Lingling; Cao, Fubin

    2018-01-01

    To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

  19. High dynamic range image acquisition based on multiplex cameras

    Science.gov (United States)

    Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

    2018-03-01

    High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

  20. Global Seismic Imaging Based on Adjoint Tomography

    Science.gov (United States)

    Bozdag, E.; Lefebvre, M.; Lei, W.; Peter, D. B.; Smith, J. A.; Zhu, H.; Komatitsch, D.; Tromp, J.

    2013-12-01

    Our aim is to perform adjoint tomography at the scale of globe to image the entire planet. We have started elastic inversions with a global data set of 253 CMT earthquakes with moment magnitudes in the range 5.8 ≤ Mw ≤ 7 and used GSN stations as well as some local networks such as USArray, European stations, etc. Using an iterative pre-conditioned conjugate gradient scheme, we initially set the aim to obtain a global crustal and mantle model with confined transverse isotropy in the upper mantle. Global adjoint tomography has so far remained a challenge mainly due to computational limitations. Recent improvements in our 3D solvers (e.g., a GPU version) and access to high-performance computational centers (e.g., ORNL's Cray XK7 "Titan" system) now enable us to perform iterations with higher-resolution (T > 9 s) and longer-duration (200 min) simulations to accommodate high-frequency body waves and major-arc surface waves, respectively, which help improve data coverage. The remaining challenge is the heavy I/O traffic caused by the numerous files generated during the forward/adjoint simulations and the pre- and post-processing stages of our workflow. We improve the global adjoint tomography workflow by adopting the ADIOS file format for our seismic data as well as models, kernels, etc., to improve efficiency on high-performance clusters. Our ultimate aim is to use data from all available networks and earthquakes within the magnitude range of our interest (5.5 ≤ Mw ≤ 7) which requires a solid framework to manage big data in our global adjoint tomography workflow. We discuss the current status and future of global adjoint tomography based on our initial results as well as practical issues such as handling big data in inversions and on high-performance computing systems.

  1. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  2. Region-based multifocus image fusion for the precise acquisition of Pap smear images.

    Science.gov (United States)

    Tello-Mijares, Santiago; Bescós, Jesús

    2018-05-01

    A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  3. Image-based automatic recognition of larvae

    Science.gov (United States)

    Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

    2010-08-01

    As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

  4. Models for Patch-Based Image Restoration

    Directory of Open Access Journals (Sweden)

    Petrovic Nemanja

    2009-01-01

    Full Text Available Abstract We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

  5. Models for Patch-Based Image Restoration

    Directory of Open Access Journals (Sweden)

    Mithun Das Gupta

    2009-01-01

    Full Text Available We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

  6. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  7. Robust histogram-based image retrieval

    Czech Academy of Sciences Publication Activity Database

    Höschl, Cyril; Flusser, Jan

    2016-01-01

    Roč. 69, č. 1 (2016), s. 72-81 ISSN 0167-8655 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : Image retrieval * Noisy image * Histogram * Convolution * Moments * Invariants Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.995, year: 2016 http://library.utia.cas.cz/separaty/2015/ZOI/hoschl-0452147.pdf

  8. Content Based Medical Image Retrieval for Histopathological, CT and MRI Images

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2013-09-01

    Full Text Available A content based approach is followed for medical images. The purpose of this study is to access the stability of these methods for medical image retrieval. The methods used in color based retrieval for histopathological images are color co-occurrence matrix (CCM and histogram with meta features. For texture based retrieval GLCM (gray level co-occurrence matrix and local binary pattern (LBP were used. For shape based retrieval canny edge detection and otsu‘s method with multivariable threshold were used. Texture and shape based retrieval were implemented using MRI (magnetic resonance images. The most remarkable characteristics of the article are its content based approach for each medical imaging modality. Our efforts were focused on the initial visual search. From our experiment, histogram with meta features in color based retrieval for histopathological images shows a precision of 60 % and recall of 30 %. Whereas GLCM in texture based retrieval for MRI images shows a precision of 70 % and recall of 20 %. Shape based retrieval for MRI images shows a precision of 50% and recall of 25 %. The retrieval results shows that this simple approach is successful.

  9. Fast image matching algorithm based on projection characteristics

    Science.gov (United States)

    Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

    2011-06-01

    Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

  10. A novel secret image sharing scheme based on chaotic system

    Science.gov (United States)

    Li, Li; Abd El-Latif, Ahmed A.; Wang, Chuanjun; Li, Qiong; Niu, Xiamu

    2012-04-01

    In this paper, we propose a new secret image sharing scheme based on chaotic system and Shamir's method. The new scheme protects the shadow images with confidentiality and loss-tolerance simultaneously. In the new scheme, we generate the key sequence based on chaotic system and then encrypt the original image during the sharing phase. Experimental results and analysis of the proposed scheme demonstrate a better performance than other schemes and confirm a high probability to resist brute force attack.

  11. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.

    Science.gov (United States)

    Inano, Rika; Oishi, Naoya; Kunieda, Takeharu; Arakawa, Yoshiki; Yamao, Yukihiro; Shibata, Sumiya; Kikuchi, Takayuki; Fukuyama, Hidenao; Miyamoto, Susumu

    2014-01-01

    Gliomas are the most common intra-axial primary brain tumour; therefore, predicting glioma grade would influence therapeutic strategies. Although several methods based on single or multiple parameters from diagnostic images exist, a definitive method for pre-operatively determining glioma grade remains unknown. We aimed to develop an unsupervised method using multiple parameters from pre-operative diffusion tensor images for obtaining a clustered image that could enable visual grading of gliomas. Fourteen patients with low-grade gliomas and 19 with high-grade gliomas underwent diffusion tensor imaging and three-dimensional T1-weighted magnetic resonance imaging before tumour resection. Seven features including diffusion-weighted imaging, fractional anisotropy, first eigenvalue, second eigenvalue, third eigenvalue, mean diffusivity and raw T2 signal with no diffusion weighting, were extracted as multiple parameters from diffusion tensor imaging. We developed a two-level clustering approach for a self-organizing map followed by the K-means algorithm to enable unsupervised clustering of a large number of input vectors with the seven features for the whole brain. The vectors were grouped by the self-organizing map as protoclusters, which were classified into the smaller number of clusters by K-means to make a voxel-based diffusion tensor-based clustered image. Furthermore, we also determined if the diffusion tensor-based clustered image was really helpful for predicting pre-operative glioma grade in a supervised manner. The ratio of each class in the diffusion tensor-based clustered images was calculated from the regions of interest manually traced on the diffusion tensor imaging space, and the common logarithmic ratio scales were calculated. We then applied support vector machine as a classifier for distinguishing between low- and high-grade gliomas. Consequently, the sensitivity, specificity, accuracy and area under the curve of receiver operating characteristic

  12. Pixel extraction based integral imaging with controllable viewing direction

    International Nuclear Information System (INIS)

    Ji, Chao-Chao; Deng, Huan; Wang, Qiong-Hua

    2012-01-01

    We propose pixel extraction based integral imaging with a controllable viewing direction. The proposed integral imaging can provide viewers three-dimensional (3D) images in a very small viewing angle. The viewing angle and the viewing direction of the reconstructed 3D images are controlled by the pixels extracted from an elemental image array. Theoretical analysis and a 3D display experiment of the viewing direction controllable integral imaging are carried out. The experimental results verify the correctness of the theory. A 3D display based on the integral imaging can protect the viewer’s privacy and has huge potential for a television to show multiple 3D programs at the same time. (paper)

  13. An Improved FCM Medical Image Segmentation Algorithm Based on MMTD

    Directory of Open Access Journals (Sweden)

    Ningning Zhou

    2014-01-01

    Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.

  14. D Reconstruction from Uav-Based Hyperspectral Images

    Science.gov (United States)

    Liu, L.; Xu, L.; Peng, J.

    2018-04-01

    Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

  15. Research on image complexity evaluation method based on color information

    Science.gov (United States)

    Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

    2017-11-01

    In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

  16. Semantic Document Image Classification Based on Valuable Text Pattern

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2011-01-01

    Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

  17. An LG-graph-based early evaluation of segmented images

    International Nuclear Information System (INIS)

    Tsitsoulis, Athanasios; Bourbakis, Nikolaos

    2012-01-01

    Image segmentation is one of the first important parts of image analysis and understanding. Evaluation of image segmentation, however, is a very difficult task, mainly because it requires human intervention and interpretation. In this work, we propose a blind reference evaluation scheme based on regional local–global (RLG) graphs, which aims at measuring the amount and distribution of detail in images produced by segmentation algorithms. The main idea derives from the field of image understanding, where image segmentation is often used as a tool for scene interpretation and object recognition. Evaluation here derives from summarization of the structural information content and not from the assessment of performance after comparisons with a golden standard. Results show measurements for segmented images acquired from three segmentation algorithms, applied on different types of images (human faces/bodies, natural environments and structures (buildings)). (paper)

  18. Single image interpolation via adaptive nonlocal sparsity-based modeling.

    Science.gov (United States)

    Romano, Yaniv; Protter, Matan; Elad, Michael

    2014-07-01

    Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

  19. Effects of image distortion correction on voxel-based morphometry

    International Nuclear Information System (INIS)

    Goto, Masami; Abe, Osamu; Kabasawa, Hiroyuki

    2012-01-01

    We aimed to show that correcting image distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of distortion correction reduces system dependency. We obtained contiguous sagittal T 1 -weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between distortion correction and brain volume using VBM. Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require correction for distortion induced by gradient nonlinearity. (author)

  20. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    Science.gov (United States)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  1. An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

    Science.gov (United States)

    Kim, Yongmin; Alexander, Thomas

    1986-06-01

    In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

  2. Image processing based detection of lung cancer on CT scan images

    Science.gov (United States)

    Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

    2017-10-01

    In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

  3. PET-based molecular imaging in neuroscience

    International Nuclear Information System (INIS)

    Jacobs, A.H.; Heiss, W.D.; Li, H.; Knoess, C.; Schaller, B.; Kracht, L.; Monfared, P.; Vollmar, S.; Bauer, B.; Wagner, R.; Graf, R.; Wienhard, K.; Winkeler, A.; Rueger, A.; Klein, M.; Hilker, R.; Galldiks, N.; Herholz, K.; Sobesky, J.

    2003-01-01

    Positron emission tomography (PET) allows non-invasive assessment of physiological, metabolic and molecular processes in humans and animals in vivo. Advances in detector technology have led to a considerable improvement in the spatial resolution of PET (1-2 mm), enabling for the first time investigations in small experimental animals such as mice. With the developments in radiochemistry and tracer technology, a variety of endogenously expressed and exogenously introduced genes can be analysed by PET. This opens up the exciting and rapidly evolving field of molecular imaging, aiming at the non-invasive localisation of a biological process of interest in normal and diseased cells in animal models and humans in vivo. The main and most intriguing advantage of molecular imaging is the kinetic analysis of a given molecular event in the same experimental subject over time. This will allow non-invasive characterisation and ''phenotyping'' of animal models of human disease at various disease stages, under certain pathophysiological stimuli and after therapeutic intervention. The potential broad applications of imaging molecular events in vivo lie in the study of cell biology, biochemistry, gene/protein function and regulation, signal transduction, transcriptional regulation and characterisation of transgenic animals. Most importantly, molecular imaging will have great implications for the identification of potential molecular therapeutic targets, in the development of new treatment strategies, and in their successful implementation into clinical application. Here, the potential impact of molecular imaging by PET in applications in neuroscience research with a special focus on neurodegeneration and neuro-oncology is reviewed. (orig.)

  4. Stereo Vision-Based High Dynamic Range Imaging Using Differently-Exposed Image Pair

    Directory of Open Access Journals (Sweden)

    Won-Jae Park

    2017-06-01

    Full Text Available In this paper, a high dynamic range (HDR imaging method based on the stereo vision system is presented. The proposed method uses differently exposed low dynamic range (LDR images captured from a stereo camera. The stereo LDR images are first converted to initial stereo HDR images using the inverse camera response function estimated from the LDR images. However, due to the limited dynamic range of the stereo LDR camera, the radiance values in under/over-exposed regions of the initial main-view (MV HDR image can be lost. To restore these radiance values, the proposed stereo matching and hole-filling algorithms are applied to the stereo HDR images. Specifically, the auxiliary-view (AV HDR image is warped by using the estimated disparity between initial the stereo HDR images and then effective hole-filling is applied to the warped AV HDR image. To reconstruct the final MV HDR, the warped and hole-filled AV HDR image is fused with the initial MV HDR image using the weight map. The experimental results demonstrate objectively and subjectively that the proposed stereo HDR imaging method provides better performance compared to the conventional method.

  5. A Novel Image Stream Cipher Based On Dynamic Substitution

    OpenAIRE

    Elsharkawi, A.; El-Sagheer, R. M.; Akah, H.; Taha, H.

    2016-01-01

    Recently, many chaos-based stream cipher algorithms have been developed. Traditional chaos stream cipher is based on XORing a generated secure random number sequence based on chaotic maps (e.g. logistic map, Bernoulli Map, Tent Map etc.) with the original image to get the encrypted image, This type of stream cipher seems to be vulnerable to chosen plaintext attacks. This paper introduces a new stream cipher algorithm based on dynamic substitution box. The new algorithm uses one substitution b...

  6. Digital Correlation based on Wavelet Transform for Image Detection

    International Nuclear Information System (INIS)

    Barba, L; Vargas, L; Torres, C; Mattos, L

    2011-01-01

    In this work is presented a method for the optimization of digital correlators to improve the characteristic detection on images using wavelet transform as well as subband filtering. It is proposed an approach of wavelet-based image contrast enhancement in order to increase the performance of digital correlators. The multiresolution representation is employed to improve the high frequency content of images taken into account the input contrast measured for the original image. The energy of correlation peaks and discrimination level of several objects are improved with this technique. To demonstrate the potentiality in extracting characteristics using the wavelet transform, small objects inside reference images are detected successfully.

  7. A framework of region-based dynamic image fusion

    Institute of Scientific and Technical Information of China (English)

    WANG Zhong-hua; QIN Zheng; LIU Yu

    2007-01-01

    A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

  8. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  9. An Image Morphing Technique Based on Optimal Mass Preserving Mapping

    Science.gov (United States)

    Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen

    2013-01-01

    Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods. PMID:17547128

  10. Multispectral image pansharpening based on the contourlet transform

    Energy Technology Data Exchange (ETDEWEB)

    Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

    2010-02-01

    Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

  11. An Effective Combined Feature For Web Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    H.M.R.B Herath

    2015-08-01

    Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

  12. Object recognition based on Google's reverse image search and image similarity

    Science.gov (United States)

    Horváth, András.

    2015-12-01

    Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

  13. Multi-viewpoint Image Array Virtual Viewpoint Rapid Generation Algorithm Based on Image Layering

    Science.gov (United States)

    Jiang, Lu; Piao, Yan

    2018-04-01

    The use of multi-view image array combined with virtual viewpoint generation technology to record 3D scene information in large scenes has become one of the key technologies for the development of integrated imaging. This paper presents a virtual viewpoint rendering method based on image layering algorithm. Firstly, the depth information of reference viewpoint image is quickly obtained. During this process, SAD is chosen as the similarity measure function. Then layer the reference image and calculate the parallax based on the depth information. Through the relative distance between the virtual viewpoint and the reference viewpoint, the image layers are weighted and panned. Finally the virtual viewpoint image is rendered layer by layer according to the distance between the image layers and the viewer. This method avoids the disadvantages of the algorithm DIBR, such as high-precision requirements of depth map and complex mapping operations. Experiments show that, this algorithm can achieve the synthesis of virtual viewpoints in any position within 2×2 viewpoints range, and the rendering speed is also very impressive. The average result proved that this method can get satisfactory image quality. The average SSIM value of the results relative to real viewpoint images can reaches 0.9525, the PSNR value can reaches 38.353 and the image histogram similarity can reaches 93.77%.

  14. Mid-infrared upconversion based hyperspectral imaging

    DEFF Research Database (Denmark)

    Junaid, Saher; Tomko, Jan; Semtsiv, Mykhaylo P.

    2018-01-01

    quantum cascade laser illumination. AgGaS2 is used as the nonlinear medium for sum frequency generation using a 1064 nm mixing laser. Angular scanning of the nonlinear crystal provides broad spectral coverage at every spatial position in the image. This study demonstrates the retrieval of series...

  15. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    Hongguang Li

    2018-01-01

    Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

  16. Adaptive radiotherapy based on contrast enhanced cone beam CT imaging

    International Nuclear Information System (INIS)

    Soevik, Aaste; Skogmo, Hege K.; Roedal, Jan; Lervaag, Christoffer; Eilertsen, Karsten; Malinen, Eirik

    2010-01-01

    Cone beam CT (CBCT) imaging has become an integral part of radiation therapy, with images typically used for offline or online patient setup corrections based on bony anatomy co-registration. Ideally, the co-registration should be based on tumor localization. However, soft tissue contrast in CBCT images may be limited. In the present work, contrast enhanced CBCT (CECBCT) images were used for tumor visualization and treatment adaptation. Material and methods. A spontaneous canine maxillary tumor was subjected to repeated cone beam CT imaging during fractionated radiotherapy (10 fractions in total). At five of the treatment fractions, CECBCT images, employing an iodinated contrast agent, were acquired, as well as pre-contrast CBCT images. The tumor was clearly visible in post-contrast minus pre-contrast subtraction images, and these contrast images were used to delineate gross tumor volumes. IMRT dose plans were subsequently generated. Four different strategies were explored: 1) fully adapted planning based on each CECBCT image series, 2) planning based on images acquired at the first treatment fraction and patient repositioning following bony anatomy co-registration, 3) as for 2), but with patient repositioning based on co-registering contrast images, and 4) a strategy with no patient repositioning or treatment adaptation. The equivalent uniform dose (EUD) and tumor control probability (TCP) calculations to estimate treatment outcome for each strategy. Results. Similar translation vectors were found when bony anatomy and contrast enhancement co-registration were compared. Strategy 1 gave EUDs closest to the prescription dose and the highest TCP. Strategies 2 and 3 gave EUDs and TCPs close to that of strategy 1, with strategy 3 being slightly better than strategy 2. Even greater benefits from strategies 1 and 3 are expected with increasing tumor movement or deformation during treatment. The non-adaptive strategy 4 was clearly inferior to all three adaptive strategies

  17. Extracting flat-field images from scene-based image sequences using phase correlation

    Energy Technology Data Exchange (ETDEWEB)

    Caron, James N., E-mail: Caron@RSImd.com [Research Support Instruments, 4325-B Forbes Boulevard, Lanham, Maryland 20706 (United States); Montes, Marcos J. [Naval Research Laboratory, Code 7231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States); Obermark, Jerome L. [Naval Research Laboratory, Code 8231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States)

    2016-06-15

    Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method uses sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.

  18. Vision communications based on LED array and imaging sensor

    Science.gov (United States)

    Yoo, Jong-Ho; Jung, Sung-Yoon

    2012-11-01

    In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.

  19. Improved image retrieval based on fuzzy colour feature vector

    Science.gov (United States)

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  20. Cross-orientation masking in human color vision: application of a two-stage model to assess dichoptic and monocular sources of suppression.

    Science.gov (United States)

    Kim, Yeon Jin; Gheiratmand, Mina; Mullen, Kathy T

    2013-05-28

    Cross-orientation masking (XOM) occurs when the detection of a test grating is masked by a superimposed grating at an orthogonal orientation, and is thought to reveal the suppressive effects mediating contrast normalization. Medina and Mullen (2009) reported that XOM was greater for chromatic than achromatic stimuli at equivalent spatial and temporal frequencies. Here we address whether the greater suppression found in binocular color vision originates from a monocular or interocular site, or both. We measure monocular and dichoptic masking functions for red-green color contrast and achromatic contrast at three different spatial frequencies (0.375, 0.75, and 1.5 cpd, 2 Hz). We fit these functions with a modified two-stage masking model (Meese & Baker, 2009) to extract the monocular and interocular weights of suppression. We find that the weight of monocular suppression is significantly higher for color than achromatic contrast, whereas dichoptic suppression is similar for both. These effects are invariant across spatial frequency. We then apply the model to the binocular masking data using the measured values of the monocular and interocular sources of suppression and show that these are sufficient to account for color binocular masking. We conclude that the greater strength of chromatic XOM has a monocular origin that transfers through to the binocular site.

  1. Retrieval Architecture with Classified Query for Content Based Image Recognition

    Directory of Open Access Journals (Sweden)

    Rik Das

    2016-01-01

    Full Text Available The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.

  2. Novel welding image processing method based on fractal theory

    Institute of Scientific and Technical Information of China (English)

    陈强; 孙振国; 肖勇; 路井荣

    2002-01-01

    Computer vision has come into used in the fields of welding process control and automation. In order to improve precision and rapidity of welding image processing, a novel method based on fractal theory has been put forward in this paper. Compared with traditional methods, the image is preliminarily processed in the macroscopic regions then thoroughly analyzed in the microscopic regions in the new method. With which, an image is divided up to some regions according to the different fractal characters of image edge, and the fuzzy regions including image edges are detected out, then image edges are identified with Sobel operator and curved by LSM (Lease Square Method). Since the data to be processed have been decreased and the noise of image has been reduced, it has been testified through experiments that edges of weld seam or weld pool could be recognized correctly and quickly.

  3. FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT

    Directory of Open Access Journals (Sweden)

    T.C. Raja Kumar

    2011-07-01

    Full Text Available Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.

  4. An FPGA-based heterogeneous image fusion system design method

    Science.gov (United States)

    Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong

    2011-08-01

    Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.

  5. Optical image encryption scheme with multiple light paths based on compressive ghost imaging

    Science.gov (United States)

    Zhu, Jinan; Yang, Xiulun; Meng, Xiangfeng; Wang, Yurong; Yin, Yongkai; Sun, Xiaowen; Dong, Guoyan

    2018-02-01

    An optical image encryption method with multiple light paths is proposed based on compressive ghost imaging. In the encryption process, M random phase-only masks (POMs) are generated by means of logistic map algorithm, and these masks are then uploaded to the spatial light modulator (SLM). The collimated laser light is divided into several beams by beam splitters as it passes through the SLM, and the light beams illuminate the secret images, which are converted into sparse images by discrete wavelet transform beforehand. Thus, the secret images are simultaneously encrypted into intensity vectors by ghost imaging. The distances between the SLM and secret images vary and can be used as the main keys with original POM and the logistic map algorithm coefficient in the decryption process. In the proposed method, the storage space can be significantly decreased and the security of the system can be improved. The feasibility, security and robustness of the method are further analysed through computer simulations.

  6. Image registration assessment in radiotherapy image guidance based on control chart monitoring.

    Science.gov (United States)

    Xia, Wenyao; Breen, Stephen L

    2018-04-01

    Image guidance with cone beam computed tomography in radiotherapy can guarantee the precision and accuracy of patient positioning prior to treatment delivery. During the image guidance process, operators need to take great effort to evaluate the image guidance quality before correcting a patient's position. This work proposes an image registration assessment method based on control chart monitoring to reduce the effort taken by the operator. According to the control chart plotted by daily registration scores of each patient, the proposed method can quickly detect both alignment errors and image quality inconsistency. Therefore, the proposed method can provide a clear guideline for the operators to identify unacceptable image quality and unacceptable image registration with minimal effort. Experimental results demonstrate that by using control charts from a clinical database of 10 patients undergoing prostate radiotherapy, the proposed method can quickly identify out-of-control signals and find special cause of out-of-control registration events.

  7. Concave omnidirectional imaging device for cylindrical object based on catadioptric panoramic imaging

    Science.gov (United States)

    Wu, Xiaojun; Wu, Yumei; Wen, Peizhi

    2018-03-01

    To obtain information on the outer surface of a cylinder object, we propose a catadioptric panoramic imaging system based on the principle of uniform spatial resolution for vertical scenes. First, the influence of the projection-equation coefficients on the spatial resolution and astigmatism of the panoramic system are discussed, respectively. Through parameter optimization, we obtain the appropriate coefficients for the projection equation, and so the imaging quality of the entire imaging system can reach an optimum value. Finally, the system projection equation is calibrated, and an undistorted rectangular panoramic image is obtained using the cylindrical-surface projection expansion method. The proposed 360-deg panoramic-imaging device overcomes the shortcomings of existing surface panoramic-imaging methods, and it has the advantages of low cost, simple structure, high imaging quality, and small distortion, etc. The experimental results show the effectiveness of the proposed method.

  8. Image Blocking Encryption Algorithm Based on Laser Chaos Synchronization

    Directory of Open Access Journals (Sweden)

    Shu-Ying Wang

    2016-01-01

    Full Text Available In view of the digital image transmission security, based on laser chaos synchronization and Arnold cat map, a novel image encryption scheme is proposed. Based on pixel values of plain image a parameter is generated to influence the secret key. Sequences of the drive system and response system are pretreated by the same method and make image blocking encryption scheme for plain image. Finally, pixels position are scrambled by general Arnold transformation. In decryption process, the chaotic synchronization accuracy is fully considered and the relationship between the effect of synchronization and decryption is analyzed, which has characteristics of high precision, higher efficiency, simplicity, flexibility, and better controllability. The experimental results show that the encryption algorithm image has high security and good antijamming performance.

  9. Lossless Image Compression Based on Multiple-Tables Arithmetic Coding

    Directory of Open Access Journals (Sweden)

    Rung-Ching Chen

    2009-01-01

    Full Text Available This paper is intended to present a lossless image compression method based on multiple-tables arithmetic coding (MTAC method to encode a gray-level image f. First, the MTAC method employs a median edge detector (MED to reduce the entropy rate of f. The gray levels of two adjacent pixels in an image are usually similar. A base-switching transformation approach is then used to reduce the spatial redundancy of the image. The gray levels of some pixels in an image are more common than those of others. Finally, the arithmetic encoding method is applied to reduce the coding redundancy of the image. To promote high performance of the arithmetic encoding method, the MTAC method first classifies the data and then encodes each cluster of data using a distinct code table. The experimental results show that, in most cases, the MTAC method provides a higher efficiency in use of storage space than the lossless JPEG2000 does.

  10. Disambiguation of Necker cube rotation by monocular and binocular depth cues: relative effectiveness for establishing long-term bias.

    Science.gov (United States)

    Harrison, Sarah J; Backus, Benjamin T; Jain, Anshul

    2011-05-11

    The apparent direction of rotation of perceptually bistable wire-frame (Necker) cubes can be conditioned to depend on retinal location by interleaving their presentation with cubes that are disambiguated by depth cues (Haijiang, Saunders, Stone, & Backus, 2006; Harrison & Backus, 2010a). The long-term nature of the learned bias is demonstrated by resistance to counter-conditioning on a consecutive day. In previous work, either binocular disparity and occlusion, or a combination of monocular depth cues that included occlusion, internal occlusion, haze, and depth-from-shading, were used to control the rotation direction of disambiguated cubes. Here, we test the relative effectiveness of these two sets of depth cues in establishing the retinal location bias. Both cue sets were highly effective in establishing a perceptual bias on Day 1 as measured by the perceived rotation direction of ambiguous cubes. The effect of counter-conditioning on Day 2, on perceptual outcome for ambiguous cubes, was independent of whether the cue set was the same or different as Day 1. This invariance suggests that a common neural population instantiates the bias for rotation direction, regardless of the cue set used. However, in a further experiment where only disambiguated cubes were presented on Day 1, perceptual outcome of ambiguous cubes during Day 2 counter-conditioning showed that the monocular-only cue set was in fact more effective than disparity-plus-occlusion for causing long-term learning of the bias. These results can be reconciled if the conditioning effect of Day 1 ambiguous trials in the first experiment is taken into account (Harrison & Backus, 2010b). We suggest that monocular disambiguation leads to stronger bias either because it more strongly activates a single neural population that is necessary for perceiving rotation, or because ambiguous stimuli engage cortical areas that are also engaged by monocularly disambiguated stimuli but not by disparity-disambiguated stimuli

  11. An Approach for Environment Mapping and Control of Wall Follower Cellbot Through Monocular Vision and Fuzzy System

    OpenAIRE

    Farias, Karoline de M.; Rodrigues Junior, WIlson Leal; Bezerra Neto, Ranulfo P.; Rabelo, Ricardo A. L.; Santana, Andre M.

    2017-01-01

    This paper presents an approach using range measurement through homography calculation to build 2D visual occupancy grid and control the robot through monocular vision. This approach is designed for a Cellbot architecture. The robot is equipped with wall following behavior to explore the environment, which enables the robot to trail objects contours, residing in the fuzzy control the responsibility to provide commands for the correct execution of the robot movements while facing the advers...

  12. Generalization of Figure-Ground Segmentation from Binocular to Monocular Vision in an Embodied Biological Brain Model

    Science.gov (United States)

    2011-08-01

    figure and ground the luminance cue breaks down and gestalt contours can fail to pop out. In this case we rely on color, which, having weak stereopsis...REPORT Generalization of Figure - Ground Segmentation from Monocular to Binocular Vision in an Embodied Biological Brain Model 14. ABSTRACT 16. SECURITY...U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS figure - ground , neural network, object

  13. Imaging system design and image interpolation based on CMOS image sensor

    Science.gov (United States)

    Li, Yu-feng; Liang, Fei; Guo, Rui

    2009-11-01

    An image acquisition system is introduced, which consists of a color CMOS image sensor (OV9620), SRAM (CY62148), CPLD (EPM7128AE) and DSP (TMS320VC5509A). The CPLD implements the logic and timing control to the system. SRAM stores the image data, and DSP controls the image acquisition system through the SCCB (Omni Vision Serial Camera Control Bus). The timing sequence of the CMOS image sensor OV9620 is analyzed. The imaging part and the high speed image data memory unit are designed. The hardware and software design of the image acquisition and processing system is given. CMOS digital cameras use color filter arrays to sample different spectral components, such as red, green, and blue. At the location of each pixel only one color sample is taken, and the other colors must be interpolated from neighboring samples. We use the edge-oriented adaptive interpolation algorithm for the edge pixels and bilinear interpolation algorithm for the non-edge pixels to improve the visual quality of the interpolated images. This method can get high processing speed, decrease the computational complexity, and effectively preserve the image edges.

  14. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

  15. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  16. Image degradation characteristics and restoration based on regularization for diffractive imaging

    Science.gov (United States)

    Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

    2017-11-01

    The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

  17. Temporal visual field defects are associated with monocular inattention in chiasmal pathology.

    Science.gov (United States)

    Fledelius, Hans C

    2009-11-01

    Chiasmal lesions have been shown to give rise occasionally to uni-ocular temporal inattention, which cannot be compensated for by volitional eye movement. This article describes the assessments of 46 such patients with chiasmal pathology. It aims to determine the clinical spectrum of this disorder, including interference with reading. Retrospective consecutive observational clinical case study over a 7-year period comprising 46 patients with chiasmal field loss of varying degrees. Observation of reading behaviour during monocular visual acuity testing ascertained from consecutive patients who appeared unable to read optotypes on the temporal side of the chart. Visual fields were evaluated by kinetic (Goldmann) and static (Octopus) techniques. Five patients who clearly manifested this condition are presented in more detail. The results of visual field testing were related to absence or presence of uni-ocular visual inattentive behaviour for distance visual acuity testing and/or reading printed text. Despite normal eye movements, the 46 patients making up the clinical series perceived only optotypes in the nasal part of the chart, in one eye or in both, when tested for each eye in turn. The temporal optotypes were ignored, and this behaviour persisted despite instruction to search for any additional letters temporal to those, which had been seen. This phenomenon of unilateral visual inattention held for both eyes in 18 and was unilateral in the remaining 28 patients. Partial or full reversibility after treatment was recorded in 21 of the 39 for whom reliable follow-up data were available. Reading a text was affected in 24 individuals, and permanently so in six. A neglect-like spatial unawareness and a lack of cognitive compensation for varying degrees of temporal visual field loss were present in all the patients observed. Not only is visual field loss a feature of chiasmal pathology, but the higher visual function of affording attention within the temporal visual

  18. Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging.

    Science.gov (United States)

    Zhang, Shuanghui; Liu, Yongxiang; Li, Xiang; Bi, Guoan

    2016-04-28

    This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.

  19. Image-based characterization of foamed polymeric tissue scaffolds

    International Nuclear Information System (INIS)

    Mather, Melissa L; Morgan, Stephen P; Crowe, John A; White, Lisa J; Shakesheff, Kevin M; Tai, Hongyun; Howdle, Steven M; Kockenberger, Walter

    2008-01-01

    Tissue scaffolds are integral to many regenerative medicine therapies, providing suitable environments for tissue regeneration. In order to assess their suitability, methods to routinely and reproducibly characterize scaffolds are needed. Scaffold structures are typically complex, and thus their characterization is far from trivial. The work presented in this paper is centred on the application of the principles of scaffold characterization outlined in guidelines developed by ASTM International. Specifically, this work demonstrates the capabilities of different imaging modalities and analysis techniques used to characterize scaffolds fabricated from poly(lactic-co-glycolic acid) using supercritical carbon dioxide. Three structurally different scaffolds were used. The scaffolds were imaged using: scanning electron microscopy, micro x-ray computed tomography, magnetic resonance imaging and terahertz pulsed imaging. In each case two-dimensional images were obtained from which scaffold properties were determined using image processing. The findings of this work highlight how the chosen imaging modality and image-processing technique can influence the results of scaffold characterization. It is concluded that in order to obtain useful results from image-based scaffold characterization, an imaging methodology providing sufficient contrast and resolution must be used along with robust image segmentation methods to allow intercomparison of results

  20. Sparse representation based image interpolation with nonlocal autoregressive modeling.

    Science.gov (United States)

    Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

    2013-04-01

    Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

  1. Novel spirometry based on optical surface imaging

    Energy Technology Data Exchange (ETDEWEB)

    Li, Guang, E-mail: lig2@mskcc.org; Huang, Hailiang; Li, Diana G.; Chen, Qing; Gaebler, Carl P.; Mechalakos, James [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Wei, Jie [Department of Computer Science, City College of New York, New York, New York 10031 (United States); Sullivan, James [Pulmonary Laboratories, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Zatcky, Joan; Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States)

    2015-04-15

    Purpose: To evaluate the feasibility of using optical surface imaging (OSI) to measure the dynamic tidal volume (TV) of the human torso during free breathing. Methods: We performed experiments to measure volume or volume change in geometric and deformable phantoms as well as human subjects using OSI. To assess the accuracy of OSI in volume determination, we performed experiments using five geometric phantoms and two deformable body phantoms and compared the values with those derived from geometric calculations and computed tomography (CT) measurements, respectively. To apply this technique to human subjects, an institutional review board protocol was established and three healthy volunteers were studied. In the human experiment, a high-speed image capture mode of OSI was applied to acquire torso images at 4–5 frames per second, which was synchronized with conventional spirometric measurements at 5 Hz. An in-house MATLAB program was developed to interactively define the volume of interest (VOI), separate the thorax and abdomen, and automatically calculate the thoracic and abdominal volumes within the VOIs. The torso volume change (TV C = ΔV{sub torso} = ΔV{sub thorax} + ΔV{sub abdomen}) was automatically calculated using full-exhalation phase as the reference. The volumetric breathing pattern (BP{sub v} = ΔV{sub thorax}/ΔV{sub torso}) quantifying thoracic and abdominal volume variations was also calculated. Under quiet breathing, TVC should equal the tidal volume measured concurrently by a spirometer with a conversion factor (1.08) accounting for internal and external differences of temperature and moisture. Another MATLAB program was implemented to control the conventional spirometer that was used as the standard. Results: The volumes measured from the OSI imaging of geometric phantoms agreed with the calculated volumes with a discrepancy of 0.0% ± 1.6% (range −1.9% to 2.5%). In measurements from the deformable torso/thorax phantoms, the volume

  2. Novel spirometry based on optical surface imaging

    International Nuclear Information System (INIS)

    Li, Guang; Huang, Hailiang; Li, Diana G.; Chen, Qing; Gaebler, Carl P.; Mechalakos, James; Wei, Jie; Sullivan, James; Zatcky, Joan; Rimner, Andreas

    2015-01-01

    Purpose: To evaluate the feasibility of using optical surface imaging (OSI) to measure the dynamic tidal volume (TV) of the human torso during free breathing. Methods: We performed experiments to measure volume or volume change in geometric and deformable phantoms as well as human subjects using OSI. To assess the accuracy of OSI in volume determination, we performed experiments using five geometric phantoms and two deformable body phantoms and compared the values with those derived from geometric calculations and computed tomography (CT) measurements, respectively. To apply this technique to human subjects, an institutional review board protocol was established and three healthy volunteers were studied. In the human experiment, a high-speed image capture mode of OSI was applied to acquire torso images at 4–5 frames per second, which was synchronized with conventional spirometric measurements at 5 Hz. An in-house MATLAB program was developed to interactively define the volume of interest (VOI), separate the thorax and abdomen, and automatically calculate the thoracic and abdominal volumes within the VOIs. The torso volume change (TV C = ΔV torso = ΔV thorax + ΔV abdomen ) was automatically calculated using full-exhalation phase as the reference. The volumetric breathing pattern (BP v = ΔV thorax /ΔV torso ) quantifying thoracic and abdominal volume variations was also calculated. Under quiet breathing, TVC should equal the tidal volume measured concurrently by a spirometer with a conversion factor (1.08) accounting for internal and external differences of temperature and moisture. Another MATLAB program was implemented to control the conventional spirometer that was used as the standard. Results: The volumes measured from the OSI imaging of geometric phantoms agreed with the calculated volumes with a discrepancy of 0.0% ± 1.6% (range −1.9% to 2.5%). In measurements from the deformable torso/thorax phantoms, the volume differences measured using OSI

  3. Image segmentation-based robust feature extraction for color image watermarking

    Science.gov (United States)

    Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

    2018-04-01

    This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

  4. Adaptive Image Transmission Scheme over Wavelet-Based OFDM System

    Institute of Scientific and Technical Information of China (English)

    GAOXinying; YUANDongfeng; ZHANGHaixia

    2005-01-01

    In this paper an adaptive image transmission scheme is proposed over Wavelet-based OFDM (WOFDM) system with Unequal error protection (UEP) by the design of non-uniform signal constellation in MLC. Two different data division schemes: byte-based and bitbased, are analyzed and compared. Different bits are protected unequally according to their different contribution to the image quality in bit-based data division scheme, which causes UEP combined with this scheme more powerful than that with byte-based scheme. Simulation results demonstrate that image transmission by UEP with bit-based data division scheme presents much higher PSNR values and surprisingly better image quality. Furthermore, by considering the tradeoff of complexity and BER performance, Haar wavelet with the shortest compactly supported filter length is the most suitable one among orthogonal Daubechies wavelet series in our proposed system.

  5. A simple polarized-based diffused reflectance colour imaging system

    African Journals Online (AJOL)

    A simple polarized-based diffuse reflectance imaging system has been developed. The system is designed for both in vivo and in vitro imaging of agricultural specimen in the visible region. The system uses a commercial web camera and a halogen lamp that makes it relatively simple and less expensive for diagnostic ...

  6. Efficient Image Blur in Web-Based Applications

    DEFF Research Database (Denmark)

    Kraus, Martin

    2010-01-01

    Scripting languages require the use of high-level library functions to implement efficient image processing; thus, real-time image blur in web-based applications is a challenging task unless specific library functions are available for this purpose. We present a pyramid blur algorithm, which can ...

  7. Geographic Object-Based Image Analysis: Towards a new paradigm

    NARCIS (Netherlands)

    Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.A.|info:eu-repo/dai/nl/224281216; Queiroz Feitosa, R.; van der Meer, F.D.|info:eu-repo/dai/nl/138940908; van der Werff, H.M.A.; van Coillie, F.; Tiede, A.

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature

  8. Reconfigurable pipelined sensing for image-based control

    NARCIS (Netherlands)

    Medina, R.; Stuijk, S.; Goswami, D.; Basten, T.

    2016-01-01

    Image-based control systems are becoming common in domains such as robotics, healthcare and industrial automation. Coping with a long sample period because of the latency of the image processing algorithm is an open challenge. Modern multi-core platforms allow to address this challenge by pipelining

  9. A World Wide Web Region-Based Image Search Engine

    DEFF Research Database (Denmark)

    Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

    2001-01-01

    In this paper the development of an intelligent image content-based search engine for the World Wide Web is presented. This system will offer a new form of media representation and access of content available in WWW. Information Web Crawlers continuously traverse the Internet and collect images...

  10. Luminescence imaging strategies for drone-based PV array inspection

    DEFF Research Database (Denmark)

    Benatto, Gisele Alves dos Reis; Riedel, Nicholas; Mantel, Claire

    2017-01-01

    The goal of this work is to perform outdoor defect detection imaging that will be used in a fast, accurate and automatic drone-based survey system for PV power plants. The imaging development focuses on techniques that do not require electrical contact, permitting automatic drone inspections...

  11. Sampling in image space for vision based SLAM

    NARCIS (Netherlands)

    Booij, O.; Zivkovic, Z.; Kröse, B.

    2008-01-01

    Loop closing in vision based SLAM applications is a difficult task. Comparing new image data with all previous image data acquired for the map is practically impossible because of the high computational costs. This problem is part of the bigger problem to acquire local geometric constraints from

  12. Wavelet-based compression of pathological images for telemedicine applications

    Science.gov (United States)

    Chen, Chang W.; Jiang, Jianfei; Zheng, Zhiyong; Wu, Xue G.; Yu, Lun

    2000-05-01

    In this paper, we present the performance evaluation of wavelet-based coding techniques as applied to the compression of pathological images for application in an Internet-based telemedicine system. We first study how well suited the wavelet-based coding is as it applies to the compression of pathological images, since these images often contain fine textures that are often critical to the diagnosis of potential diseases. We compare the wavelet-based compression with the DCT-based JPEG compression in the DICOM standard for medical imaging applications. Both objective and subjective measures have been studied in the evaluation of compression performance. These studies are performed in close collaboration with expert pathologists who have conducted the evaluation of the compressed pathological images and communication engineers and information scientists who designed the proposed telemedicine system. These performance evaluations have shown that the wavelet-based coding is suitable for the compression of various pathological images and can be integrated well with the Internet-based telemedicine systems. A prototype of the proposed telemedicine system has been developed in which the wavelet-based coding is adopted for the compression to achieve bandwidth efficient transmission and therefore speed up the communications between the remote terminal and the central server of the telemedicine system.

  13. Personal identification based on blood vessels of retinal fundus images

    Science.gov (United States)

    Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

    2008-03-01

    Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

  14. Despeckling Polsar Images Based on Relative Total Variation Model

    Science.gov (United States)

    Jiang, C.; He, X. F.; Yang, L. J.; Jiang, J.; Wang, D. Y.; Yuan, Y.

    2018-04-01

    Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

  15. Content-based image retrieval with ontological ranking

    Science.gov (United States)

    Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

    2010-02-01

    Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping

  16. Multi-band Image Registration Method Based on Fourier Transform

    Institute of Scientific and Technical Information of China (English)

    庹红娅; 刘允才

    2004-01-01

    This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.

  17. Contour extraction of echocardiographic images based on pre-processing

    Energy Technology Data Exchange (ETDEWEB)

    Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana [Department of Multimedia, Faculty of Computer Science and Information Technology, Department of Computer and Communication Systems Engineering, Faculty of Engineering University Putra Malaysia 43400 Serdang, Selangor (Malaysia); Zamrin, D M [Department of Surgery, Faculty of Medicine, National University of Malaysia, 56000 Cheras, Kuala Lumpur (Malaysia); Saripan, M Iqbal

    2011-02-15

    In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

  18. Contour extraction of echocardiographic images based on pre-processing

    International Nuclear Information System (INIS)

    Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana; Zamrin, D M; Saripan, M Iqbal

    2011-01-01

    In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

  19. A Subdivision-Based Representation for Vector Image Editing.

    Science.gov (United States)

    Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

    2012-11-01

    Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

  20. A novel image encryption scheme based on spatial chaos map

    International Nuclear Information System (INIS)

    Sun Fuyan; Liu Shutang; Li Zhongqin; Lue Zongwang

    2008-01-01

    In recent years, the chaos-based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. In this paper, spatial chaos system are used for high degree security image encryption while its speed is acceptable. The proposed algorithm is described in detail. The basic idea is to encrypt the image in space with spatial chaos map pixel by pixel, and then the pixels are confused in multiple directions of space. Using this method one cycle, the image becomes indistinguishable in space due to inherent properties of spatial chaotic systems. Several experimental results, key sensitivity tests, key space analysis, and statistical analysis show that the approach for image cryptosystems provides an efficient and secure way for real time image encryption and transmission from the cryptographic viewpoint

  1. Image based method for aberration measurement of lithographic tools

    Science.gov (United States)

    Xu, Shuang; Tao, Bo; Guo, Yongxing; Li, Gongfa

    2018-01-01

    Information of lens aberration of lithographic tools is important as it directly affects the intensity distribution in the image plane. Zernike polynomials are commonly used for a mathematical description of lens aberrations. Due to the advantage of lower cost and easier implementation of tools, image based measurement techniques have been widely used. Lithographic tools are typically partially coherent systems that can be described by a bilinear model, which entails time consuming calculations and does not lend a simple and intuitive relationship between lens aberrations and the resulted images. Previous methods for retrieving lens aberrations in such partially coherent systems involve through-focus image measurements and time-consuming iterative algorithms. In this work, we propose a method for aberration measurement in lithographic tools, which only requires measuring two images of intensity distribution. Two linear formulations are derived in matrix forms that directly relate the measured images to the unknown Zernike coefficients. Consequently, an efficient non-iterative solution is obtained.

  2. Medical image security using modified chaos-based cryptography approach

    Science.gov (United States)

    Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

    2018-05-01

    The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

  3. Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

    Science.gov (United States)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-01-01

    To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

  4. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  5. Image Inpainting Based on Coherence Transport with Adapted Distance Functions

    KAUST Repository

    Mä rz, Thomas

    2011-01-01

    We discuss an extension of our method image inpainting based on coherence transport. For the latter method the pixels of the inpainting domain have to be serialized into an ordered list. Until now, to induce the serialization we have used

  6. X-ray detectors based on image sensors

    International Nuclear Information System (INIS)

    Costa, A.P.R.

    1983-01-01

    X-ray detectors based on image sensors are described and a comparison is made between the advantages and the disadvantages of such a kind of detectors with the position sensitive detectors. (L.C.) [pt

  7. Hardware Realization of Chaos Based Symmetric Image Encryption

    KAUST Repository

    Barakat, Mohamed L.

    2012-01-01

    This thesis presents a novel work on hardware realization of symmetric image encryption utilizing chaos based continuous systems as pseudo random number generators. Digital implementation of chaotic systems results in serious degradations

  8. Synaptic Mechanisms of Activity-Dependent Remodeling in Visual Cortex during Monocular Deprivation

    Directory of Open Access Journals (Sweden)

    Cynthia D. Rittenhouse

    2009-01-01

    Full Text Available It has long been appreciated that in the visual cortex, particularly within a postnatal critical period for experience-dependent plasticity, the closure of one eye results in a shift in the responsiveness of cortical cells toward the experienced eye. While the functional aspects of this ocular dominance shift have been studied for many decades, their cortical substrates and synaptic mechanisms remain elusive. Nonetheless, it is becoming increasingly clear that ocular dominance plasticity is a complex phenomenon that appears to have an early and a late component. Early during monocular deprivation, deprived eye cortical synapses depress, while later during the deprivation open eye synapses potentiate. Here we review current literature on the cortical mechanisms of activity-dependent plasticity in the visual system during the critical period. These studies shed light on the role of activity in shaping neuronal structure and function in general and can lead to insights regarding how learning is acquired and maintained at the neuronal level during normal and pathological brain development.

  9. [Effect of acupuncture on pattern-visual evoked potential in rats with monocular visual deprivation].

    Science.gov (United States)

    Yan, Xing-Ke; Dong, Li-Li; Liu, An-Guo; Wang, Jun-Yan; Ma, Chong-Bing; Zhu, Tian-Tian

    2013-08-01

    To explore electrophysiology mechanism of acupuncture for treatment and prevention of visual deprivation effect. Eighteen healthy 15-day Evans rats were randomly divided into a normal group, a model group and an acupuncture group, 6 rats in each one. Deprivation amblyopia model was established by monocular eyelid suture in the model group and acupuncture group. Acupuncture was applied at "Jingming" (BL 1), "Chengqi" (ST 1), "Qiuhou" (EX-HN 7) and "Cuanzhu" (BL 2) in the acupuncture group. The bilateral acupoints were selected alternately, one side for a day, and totally 14 days were required. The effect of acupuncture on visual evoked potential in different spatial frequencies was observed. Under three different kinds of spatial frequencies of 2 X 2, 4 X 4 and 8 X 8, compared with normal group, there was obvious visual deprivation effect in the model group where P1 peak latency was delayed (P0.05). Under spatial frequency of 4 X 4, N1-P1 amplitude value was maximum in the normal group and acupuncture group. With this spatial frequency the rat's eye had best resolving ability, indicating it could be the best spatial frequency for rat visual system. The visual system has obvious electrophysiology plasticity in sensitive period. Acupuncture treatment could adjust visual deprivation-induced suppression and slow of visual response in order to antagonism deprivation effect.

  10. Iris Image Classification Based on Hierarchical Visual Codebook.

    Science.gov (United States)

    Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

    2014-06-01

    Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

  11. Smart Images Search based on Visual Features Fusion

    International Nuclear Information System (INIS)

    Saad, M.H.

    2013-01-01

    Image search engines attempt to give fast and accurate access to the wide range of the huge amount images available on the Internet. There have been a number of efforts to build search engines based on the image content to enhance search results. Content-Based Image Retrieval (CBIR) systems have achieved a great interest since multimedia files, such as images and videos, have dramatically entered our lives throughout the last decade. CBIR allows automatically extracting target images according to objective visual contents of the image itself, for example its shapes, colors and textures to provide more accurate ranking of the results. The recent approaches of CBIR differ in terms of which image features are extracted to be used as image descriptors for matching process. This thesis proposes improvements of the efficiency and accuracy of CBIR systems by integrating different types of image features. This framework addresses efficient retrieval of images in large image collections. A comparative study between recent CBIR techniques is provided. According to this study; image features need to be integrated to provide more accurate description of image content and better image retrieval accuracy. In this context, this thesis presents new image retrieval approaches that provide more accurate retrieval accuracy than previous approaches. The first proposed image retrieval system uses color, texture and shape descriptors to form the global features vector. This approach integrates the yc b c r color histogram as a color descriptor, the modified Fourier descriptor as a shape descriptor and modified Edge Histogram as a texture descriptor in order to enhance the retrieval results. The second proposed approach integrates the global features vector, which is used in the first approach, with the SURF salient point technique as local feature. The nearest neighbor matching algorithm with a proposed similarity measure is applied to determine the final image rank. The second approach

  12. A data grid for imaging-based clinical trials

    Science.gov (United States)

    Zhou, Zheng; Chao, Sander S.; Lee, Jasper; Liu, Brent; Documet, Jorge; Huang, H. K.

    2007-03-01

    Clinical trials play a crucial role in testing new drugs or devices in modern medicine. Medical imaging has also become an important tool in clinical trials because images provide a unique and fast diagnosis with visual observation and quantitative assessment. A typical imaging-based clinical trial consists of: 1) A well-defined rigorous clinical trial protocol, 2) a radiology core that has a quality control mechanism, a biostatistics component, and a server for storing and distributing data and analysis results; and 3) many field sites that generate and send image studies to the radiology core. As the number of clinical trials increases, it becomes a challenge for a radiology core servicing multiple trials to have a server robust enough to administrate and quickly distribute information to participating radiologists/clinicians worldwide. The Data Grid can satisfy the aforementioned requirements of imaging based clinical trials. In this paper, we present a Data Grid architecture for imaging-based clinical trials. A Data Grid prototype has been implemented in the Image Processing and Informatics (IPI) Laboratory at the University of Southern California to test and evaluate performance in storing trial images and analysis results for a clinical trial. The implementation methodology and evaluation protocol of the Data Grid are presented.

  13. Neurophysiological Based Methods of Guided Image Search

    National Research Council Canada - National Science Library

    Marchak, Frank

    2003-01-01

    .... We developed a model of visual feature detection, the Neuronal Synchrony Model, based on neurophysiological models of temporal neuronal processing, to improve the accuracy of automatic detection...

  14. MISTICA: Minimum Spanning Tree-Based Coarse Image Alignment for Microscopy Image Sequences.

    Science.gov (United States)

    Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T

    2016-11-01

    Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to reorder the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by the way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries.

  15. Scintillator Based Coded-Aperture Imaging for Neutron Detection

    International Nuclear Information System (INIS)

    Hayes, Sean-C.; Gamage, Kelum-A-A.

    2013-06-01

    In this paper we are going to assess the variations of neutron images using a series of Monte Carlo simulations. We are going to study neutron images of the same neutron source with different source locations, using a scintillator based coded-aperture system. The Monte Carlo simulations have been conducted making use of the EJ-426 neutron scintillator detector. This type of detector has a low sensitivity to gamma rays and is therefore of particular use in a system with a source that emits a mixed radiation field. From the use of different source locations, several neutron images have been produced, compared both qualitatively and quantitatively for each case. This allows conclusions to be drawn on how suited the scintillator based coded-aperture neutron imaging system is to detecting various neutron source locations. This type of neutron imaging system can be easily used to identify and locate nuclear materials precisely. (authors)

  16. Contrast-based sensorless adaptive optics for retinal imaging.

    Science.gov (United States)

    Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

    2015-09-01

    Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

  17. Design of CMOS imaging system based on FPGA

    Science.gov (United States)

    Hu, Bo; Chen, Xiaolai

    2017-10-01

    In order to meet the needs of engineering applications for high dynamic range CMOS camera under the rolling shutter mode, a complete imaging system is designed based on the CMOS imaging sensor NSC1105. The paper decides CMOS+ADC+FPGA+Camera Link as processing architecture and introduces the design and implementation of the hardware system. As for camera software system, which consists of CMOS timing drive module, image acquisition module and transmission control module, the paper designs in Verilog language and drives it to work properly based on Xilinx FPGA. The ISE 14.6 emulator ISim is used in the simulation of signals. The imaging experimental results show that the system exhibits a 1280*1024 pixel resolution, has a frame frequency of 25 fps and a dynamic range more than 120dB. The imaging quality of the system satisfies the requirement of the index.

  18. Image Mosaic Method Based on SIFT Features of Line Segment

    Directory of Open Access Journals (Sweden)

    Jun Zhu

    2014-01-01

    Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  19. Matrix-based image reconstruction methods for tomography

    International Nuclear Information System (INIS)

    Llacer, J.; Meng, J.D.

    1984-10-01

    Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

  20. Example-Based Image Colorization Using Locality Consistent Sparse Representation.

    Science.gov (United States)

    Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

    2017-11-01

    Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

  1. Color-Based Image Retrieval from High-Similarity Image Databases

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg; Carstensen, Jens Michael

    2003-01-01

    Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce...... a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita (JM) distances between distributions of color (and color derivatives) estimated from a set of automatically extracted image regions. The weight coefficients are estimated based on optimal retrieval...... performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition....

  2. An Efficient Evolutionary Based Method For Image Segmentation

    OpenAIRE

    Aslanzadeh, Roohollah; Qazanfari, Kazem; Rahmati, Mohammad

    2017-01-01

    The goal of this paper is to present a new efficient image segmentation method based on evolutionary computation which is a model inspired from human behavior. Based on this model, a four layer process for image segmentation is proposed using the split/merge approach. In the first layer, an image is split into numerous regions using the watershed algorithm. In the second layer, a co-evolutionary process is applied to form centers of finals segments by merging similar primary regions. In the t...

  3. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  4. Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging.

    Science.gov (United States)

    Liu, Fang; Jang, Hyungseok; Kijowski, Richard; Bradshaw, Tyler; McMillan, Alan B

    2018-02-01

    Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic resonance (MR) imaging-based attenuation correction (AC) (termed deep MRAC) in brain positron emission tomography (PET)/MR imaging. Materials and Methods A PET/MR imaging AC pipeline was built by using a deep learning approach to generate pseudo computed tomographic (CT) scans from MR images. A deep convolutional auto-encoder network was trained to identify air, bone, and soft tissue in volumetric head MR images coregistered to CT data for training. A set of 30 retrospective three-dimensional T1-weighted head images was used to train the model, which was then evaluated in 10 patients by comparing the generated pseudo CT scan to an acquired CT scan. A prospective study was carried out for utilizing simultaneous PET/MR imaging for five subjects by using the proposed approach. Analysis of covariance and paired-sample t tests were used for statistical analysis to compare PET reconstruction error with deep MRAC and two existing MR imaging-based AC approaches with CT-based AC. Results Deep MRAC provides an accurate pseudo CT scan with a mean Dice coefficient of 0.971 ± 0.005 for air, 0.936 ± 0.011 for soft tissue, and 0.803 ± 0.021 for bone. Furthermore, deep MRAC provides good PET results, with average errors of less than 1% in most brain regions. Significantly lower PET reconstruction errors were realized with deep MRAC (-0.7% ± 1.1) compared with Dixon-based soft-tissue and air segmentation (-5.8% ± 3.1) and anatomic CT-based template registration (-4.8% ± 2.2). Conclusion The authors developed an automated approach that allows generation of discrete-valued pseudo CT scans (soft tissue, bone, and air) from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging. This deep learning approach for MR imaging-based AC provided reduced PET reconstruction error relative to a CT-based standard within the brain compared

  5. Measurable realistic image-based 3D mapping

    Science.gov (United States)

    Liu, W.; Wang, J.; Wang, J. J.; Ding, W.; Almagbile, A.

    2011-12-01

    Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable

  6. Imaged-Based Visual Servo Control for a VTOL Aircraft

    Directory of Open Access Journals (Sweden)

    Liying Zou

    2017-01-01

    Full Text Available This paper presents a novel control strategy to force a vertical take-off and landing (VTOL aircraft to accomplish the pinpoint landing task. The control development is based on the image-based visual servoing method and the back-stepping technique; its design differs from the existing methods because the controller maps the image errors onto the actuator space via a visual model which does not contain the depth information of the feature point. The novelty of the proposed method is to extend the image-based visual servoing technique to the VTOL aircraft control. In addition, the Lyapunov theory is used to prove the asymptotic stability of the VTOL aircraft visual servoing system, while the image error can converge to zero. Furthermore, simulations have been also conducted to demonstrate the performances of the proposed method.

  7. Level set method for image segmentation based on moment competition

    Science.gov (United States)

    Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

    2015-05-01

    We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

  8. Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI)

    International Nuclear Information System (INIS)

    Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

    2007-01-01

    Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting

  9. The Use of QBIC Content-Based Image Retrieval System

    Directory of Open Access Journals (Sweden)

    Ching-Yi Wu

    2004-03-01

    Full Text Available The fast increase in digital images has caught increasing attention on the development of image retrieval technologies. Content-based image retrieval (CBIR has become an important approach in retrieving image data from a large collection. This article reports our results on the use and users study of a CBIR system. Thirty-eight students majored in art and design were invited to use the IBM’s OBIC (Query by Image Content system through the Internet. Data from their information needs, behaviors, and retrieval strategies were collected through an in-depth interview, observation, and self-described think-aloud process. Important conclusions are:(1)There are four types of information needs for image data: implicit, inspirational, ever-changing, and purposive. The types of needs may change during the retrieval process. (2)CBIR is suitable for the example-type query, text retrieval is suitable for the scenario-type query, and image browsing is suitable for the symbolic query. (3)Different from text retrieval, detailed description of the query condition may lead to retrieval failure more easily. (4)CBIR is suitable for the domain-specific image collection, not for the images on the Word-Wide Web.[Article content in Chinese

  10. Analyser-based x-ray imaging for biomedical research

    International Nuclear Information System (INIS)

    Suortti, Pekka; Keyriläinen, Jani; Thomlinson, William

    2013-01-01

    Analyser-based imaging (ABI) is one of the several phase-contrast x-ray imaging techniques being pursued at synchrotron radiation facilities. With advancements in compact source technology, there is a possibility that ABI will become a clinical imaging modality. This paper presents the history of ABI as it has developed from its laboratory source to synchrotron imaging. The fundamental physics of phase-contrast imaging is presented both in a general sense and specifically for ABI. The technology is dependent on the use of perfect crystal monochromator optics. The theory of the x-ray optics is developed and presented in a way that will allow optimization of the imaging for specific biomedical systems. The advancement of analytical algorithms to produce separate images of the sample absorption, refraction angle map and small-angle x-ray scattering is detailed. Several detailed applications to biomedical imaging are presented to illustrate the broad range of systems and body sites studied preclinically to date: breast, cartilage and bone, soft tissue and organs. Ultimately, the application of ABI in clinical imaging will depend partly on the availability of compact sources with sufficient x-ray intensity comparable with that of the current synchrotron environment. (paper)

  11. A New Wavelet-Based Document Image Segmentation Scheme

    Institute of Scientific and Technical Information of China (English)

    赵健; 李道京; 俞卞章; 耿军平

    2002-01-01

    The document image segmentation is very useful for printing, faxing and data processing. An algorithm is developed for segmenting and classifying document image. Feature used for classification is based on the histogram distribution pattern of different image classes. The important attribute of the algorithm is using wavelet correlation image to enhance raw image's pattern, so the classification accuracy is improved. In this paper document image is divided into four types: background, photo, text and graph. Firstly, the document image background has been distingusished easily by former normally method; secondly, three image types will be distinguished by their typical histograms, in order to make histograms feature clearer, each resolution' s HH wavelet subimage is used to add to the raw image at their resolution. At last, the photo, text and praph have been devided according to how the feature fit to the Laplacian distrbution by -X2 and L. Simulations show that classification accuracy is significantly improved. The comparison with related shows that our algorithm provides both lower classification error rates and better visual results.

  12. Complex adaptation-based LDR image rendering for 3D image reconstruction

    Science.gov (United States)

    Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

    2014-07-01

    A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

  13. VISION BASED OBSTACLE DETECTION IN UAV IMAGING

    Directory of Open Access Journals (Sweden)

    S. Badrloo

    2017-08-01

    Full Text Available Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

  14. Astronomical Image Compression Techniques Based on ACC and KLT Coder

    Directory of Open Access Journals (Sweden)

    J. Schindler

    2011-01-01

    Full Text Available This paper deals with a compression of image data in applications in astronomy. Astronomical images have typical specific properties — high grayscale bit depth, size, noise occurrence and special processing algorithms. They belong to the class of scientific images. Their processing and compression is quite different from the classical approach of multimedia image processing. The database of images from BOOTES (Burst Observer and Optical Transient Exploring System has been chosen as a source of the testing signal. BOOTES is a Czech-Spanish robotic telescope for observing AGN (active galactic nuclei and the optical transient of GRB (gamma ray bursts searching. This paper discusses an approach based on an analysis of statistical properties of image data. A comparison of two irrelevancy reduction methods is presented from a scientific (astrometric and photometric point of view. The first method is based on a statistical approach, using the Karhunen-Loeve transform (KLT with uniform quantization in the spectral domain. The second technique is derived from wavelet decomposition with adaptive selection of used prediction coefficients. Finally, the comparison of three redundancy reduction methods is discussed. Multimedia format JPEG2000 and HCOMPRESS, designed especially for astronomical images, are compared with the new Astronomical Context Coder (ACC coder based on adaptive median regression.

  15. Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement

    Directory of Open Access Journals (Sweden)

    V. Magudeeswaran

    2013-01-01

    Full Text Available Fuzzy logic-based histogram equalization (FHE is proposed for image contrast enhancement. The FHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two subhistograms based on the median value of the original image and then equalizes them independently to preserve image brightness. The qualitative and quantitative analyses of proposed FHE algorithm are evaluated using two well-known parameters like average information contents (AIC and natural image quality evaluator (NIQE index for various images. From the qualitative and quantitative measures, it is interesting to see that this proposed method provides optimum results by giving better contrast enhancement and preserving the local information of the original image. Experimental result shows that the proposed method can effectively and significantly eliminate washed-out appearance and adverse artifacts induced by several existing methods. The proposed method has been tested using several images and gives better visual quality as compared to the conventional methods.

  16. Image-based fingerprint verification system using LabVIEW

    Directory of Open Access Journals (Sweden)

    Sunil K. Singla

    2008-09-01

    Full Text Available Biometric-based identification/verification systems provide a solution to the security concerns in the modern world where machine is replacing human in every aspect of life. Fingerprints, because of their uniqueness, are the most widely used and highly accepted biometrics. Fingerprint biometric systems are either minutiae-based or pattern learning (image based. The minutiae-based algorithm depends upon the local discontinuities in the ridge flow pattern and are used when template size is important while image-based matching algorithm uses both the micro and macro feature of a fingerprint and is used if fast response is required. In the present paper an image-based fingerprint verification system is discussed. The proposed method uses a learning phase, which is not present in conventional image-based systems. The learning phase uses pseudo random sub-sampling, which reduces the number of comparisons needed in the matching stage. This system has been developed using LabVIEW (Laboratory Virtual Instrument Engineering Workbench toolbox version 6i. The availability of datalog files in LabVIEW makes it one of the most promising candidates for its usage as a database. Datalog files can access and manipulate data and complex data structures quickly and easily. It makes writing and reading much faster. After extensive experimentation involving a large number of samples and different learning sizes, high accuracy with learning image size of 100 100 and a threshold value of 700 (1000 being the perfect match has been achieved.

  17. Histological image classification using biologically interpretable shape-based features

    International Nuclear Information System (INIS)

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  18. RESEARCH ON FOREST FLAME RECOGNITION ALGORITHM BASED ON IMAGE FEATURE

    Directory of Open Access Journals (Sweden)

    Z. Wang

    2017-09-01

    Full Text Available In recent years, fire recognition based on image features has become a hotspot in fire monitoring. However, due to the complexity of forest environment, the accuracy of forest fireworks recognition based on image features is low. Based on this, this paper proposes a feature extraction algorithm based on YCrCb color space and K-means clustering. Firstly, the paper prepares and analyzes the color characteristics of a large number of forest fire image samples. Using the K-means clustering algorithm, the forest flame model is obtained by comparing the two commonly used color spaces, and the suspected flame area is discriminated and extracted. The experimental results show that the extraction accuracy of flame area based on YCrCb color model is higher than that of HSI color model, which can be applied in different scene forest fire identification, and it is feasible in practice.

  19. Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

    Science.gov (United States)

    Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

    2017-07-28

    New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

  20. Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology

    Directory of Open Access Journals (Sweden)

    Vollmer Ekkehard

    2008-04-01

    Full Text Available Abstract Background Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis. Aims To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology. Theory and experiences Images used in tissue-based diagnosis present with pathology – specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease – image combination, human – diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image

  1. SU-E-J-237: Image Feature Based DRR and Portal Image Registration

    Energy Technology Data Exchange (ETDEWEB)

    Wang, X; Chang, J [NY Weill Cornell Medical Ctr, NY (United States)

    2014-06-01

    Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thus the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.

  2. Image-Based Geometric Modeling and Mesh Generation

    CERN Document Server

    2013-01-01

    As a new interdisciplinary research area, “image-based geometric modeling and mesh generation” integrates image processing, geometric modeling and mesh generation with finite element method (FEM) to solve problems in computational biomedicine, materials sciences and engineering. It is well known that FEM is currently well-developed and efficient, but mesh generation for complex geometries (e.g., the human body) still takes about 80% of the total analysis time and is the major obstacle to reduce the total computation time. It is mainly because none of the traditional approaches is sufficient to effectively construct finite element meshes for arbitrarily complicated domains, and generally a great deal of manual interaction is involved in mesh generation. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion,...

  3. Chaotic Image Encryption Algorithm Based on Circulant Operation

    Directory of Open Access Journals (Sweden)

    Xiaoling Huang

    2013-01-01

    Full Text Available A novel chaotic image encryption scheme based on the time-delay Lorenz system is presented in this paper with the description of Circulant matrix. Making use of the chaotic sequence generated by the time-delay Lorenz system, the pixel permutation is carried out in diagonal and antidiagonal directions according to the first and second components. Then, a pseudorandom chaotic sequence is generated again from time-delay Lorenz system using all components. Modular operation is further employed for diffusion by blocks, in which the control parameter is generated depending on the plain-image. Numerical experiments show that the proposed scheme possesses the properties of a large key space to resist brute-force attack, sensitive dependence on secret keys, uniform distribution of gray values in the cipher-image, and zero correlation between two adjacent cipher-image pixels. Therefore, it can be adopted as an effective and fast image encryption algorithm.

  4. 3D reconstruction based on light field images

    Science.gov (United States)

    Zhu, Dong; Wu, Chunhong; Liu, Yunluo; Fu, Dongmei

    2018-04-01

    This paper proposed a method of reconstructing three-dimensional (3D) scene from two light field images capture by Lytro illium. The work was carried out by first extracting the sub-aperture images from light field images and using the scale-invariant feature transform (SIFT) for feature registration on the selected sub-aperture images. Structure from motion (SFM) algorithm is further used on the registration completed sub-aperture images to reconstruct the three-dimensional scene. 3D sparse point cloud was obtained in the end. The method shows that the 3D reconstruction can be implemented by only two light field camera captures, rather than at least a dozen times captures by traditional cameras. This can effectively solve the time-consuming, laborious issues for 3D reconstruction based on traditional digital cameras, to achieve a more rapid, convenient and accurate reconstruction.

  5. Chaotic Image Scrambling Algorithm Based on S-DES

    International Nuclear Information System (INIS)

    Yu, X Y; Zhang, J; Ren, H E; Xu, G S; Luo, X Y

    2006-01-01

    With the security requirement improvement of the image on the network, some typical image encryption methods can't meet the demands of encryption, such as Arnold cat map and Hilbert transformation. S-DES system can encrypt the input binary flow of image, but the fixed system structure and few keys will still bring some risks. However, the sensitivity of initial value that Logistic chaotic map can be well applied to the system of S-DES, which makes S-DES have larger random and key quantities. A dual image encryption algorithm based on S-DES and Logistic map is proposed. Through Matlab simulation experiments, the key quantities will attain 10 17 and the encryption speed of one image doesn't exceed one second. Compared to traditional methods, it has some merits such as easy to understand, rapid encryption speed, large keys and sensitivity to initial value

  6. Neutron imaging system based on a video camera

    International Nuclear Information System (INIS)

    Dinca, M.

    2004-01-01

    The non-destructive testing with cold, thermal, epithermal or fast neutrons is nowadays more and more useful because the world-wide level of industrial development requires considerably higher standards of quality of manufactured products and reliability of technological processes especially where any deviation from standards could result in large-scale catastrophic consequences or human loses. Thanks to their properties, easily obtained and very good discrimination of the materials that penetrate, the thermal neutrons are the most used probe. The methods involved for this technique have advanced from neutron radiography based on converter screens and radiological films to neutron radioscopy based on video cameras, that is, from static images to dynamic images. Many neutron radioscopy systems have been used in the past with various levels of success. The quality of an image depends on the quality of the neutron beam and the type of the neutron imaging system. For real time investigations there are involved tube type cameras, CCD cameras and recently CID cameras that capture the image from an appropriate scintillator through the agency of a mirror. The analog signal of the camera is then converted into digital signal by the signal processing technology included into the camera. The image acquisition card or frame grabber from a PC converts the digital signal into an image. The image is formatted and processed by image analysis software. The scanning position of the object is controlled by the computer that commands the electrical motors that move horizontally, vertically and rotate the table of the object. Based on this system, a lot of static image acquisitions, real time non-destructive investigations of dynamic processes and finally, tomographic investigations of the small objects are done in a short time. A system based on a CID camera is presented. Fundamental differences between CCD and CID cameras lie in their pixel readout structure and technique. CIDs

  7. An improved image non-blind image deblurring method based on FoEs

    Science.gov (United States)

    Zhu, Qidan; Sun, Lei

    2013-03-01

    Traditional non-blind image deblurring algorithms always use maximum a posterior(MAP). MAP estimates involving natural image priors can reduce the ripples effectively in contrast to maximum likelihood(ML). However, they have been found lacking in terms of restoration performance. Based on this issue, we utilize MAP with KL penalty to replace traditional MAP. We develop an image reconstruction algorithm that minimizes the KL divergence between the reference distribution and the prior distribution. The approximate KL penalty can restrain over-smooth caused by MAP. We use three groups of images and Harris corner detection to prove our method. The experimental results show that our algorithm of non-blind image restoration can effectively reduce the ringing effect and exhibit the state-of-the-art deblurring results.

  8. Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer.

    Science.gov (United States)

    Gutman, David A; Dunn, William D; Cobb, Jake; Stoner, Richard M; Kalpathy-Cramer, Jayashree; Erickson, Bradley

    2014-01-01

    Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.

  9. Image Re-Ranking Based on Topic Diversity.

    Science.gov (United States)

    Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

    2017-08-01

    Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

  10. Decision-Making Based on Emotional Images

    OpenAIRE

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

  11. Decision making based on emotional images

    OpenAIRE

    Kentaro eKatahira; Kentaro eKatahira; Kentaro eKatahira; Tomomi eFujimura; Tomomi eFujimura; Kazuo eOkanoya; Kazuo eOkanoya; Kazuo eOkanoya; Masato eOkada; Masato eOkada; Masato eOkada

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

  12. Decision-making based on emotional images.

    Science.gov (United States)

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

  13. SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

    2016-06-15

    Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

  14. SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

    International Nuclear Information System (INIS)

    Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L

    2016-01-01

    Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

  15. Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qiang; Niu, Sijie [School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094 (China); Yuan, Songtao; Fan, Wen, E-mail: fanwen1029@163.com; Liu, Qinghuai [Department of Ophthalmology, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029 (China)

    2016-04-15

    Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.

  16. Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

    International Nuclear Information System (INIS)

    Chen, Qiang; Niu, Sijie; Yuan, Songtao; Fan, Wen; Liu, Qinghuai

    2016-01-01

    Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.

  17. Preoperative magnetic resonance imaging protocol for endoscopic cranial base image-guided surgery.

    Science.gov (United States)

    Grindle, Christopher R; Curry, Joseph M; Kang, Melissa D; Evans, James J; Rosen, Marc R

    2011-01-01

    Despite the increasing utilization of image-guided surgery, no radiology protocols for obtaining magnetic resonance (MR) imaging of adequate quality are available in the current literature. At our institution, more than 300 endonasal cranial base procedures including pituitary, extended pituitary, and other anterior skullbase procedures have been performed in the past 3 years. To facilitate and optimize preoperative evaluation and assessment, there was a need to develop a magnetic resonance protocol. Retrospective Technical Assessment was performed. Through a collaborative effort between the otolaryngology, neurosurgery, and neuroradiology departments at our institution, a skull base MR image-guided (IGS) protocol was developed with several ends in mind. First, it was necessary to generate diagnostic images useful for the more frequently seen pathologies to improve work flow and limit the expense and inefficiency of case specific MR studies. Second, it was necessary to generate sequences useful for IGS, preferably using sequences that best highlight that lesion. Currently, at our institution, all MR images used for IGS are obtained using this protocol as part of preoperative planning. The protocol that has been developed allows for thin cut precontrast and postcontrast axial cuts that can be used to plan intraoperative image guidance. It also obtains a thin cut T2 axial series that can be compiled separately for intraoperative imaging, or may be fused with computed tomographic images for combined modality. The outlined protocol obtains image sequences effective for diagnostic and operative purposes for image-guided surgery using both T1 and T2 sequences. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. A similarity-based data warehousing environment for medical images.

    Science.gov (United States)

    Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

    2015-11-01

    A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. SIP: A Web-Based Astronomical Image Processing Program

    Science.gov (United States)

    Simonetti, J. H.

    1999-12-01

    I have written an astronomical image processing and analysis program designed to run over the internet in a Java-compatible web browser. The program, Sky Image Processor (SIP), is accessible at the SIP webpage (http://www.phys.vt.edu/SIP). Since nothing is installed on the user's machine, there is no need to download upgrades; the latest version of the program is always instantly available. Furthermore, the Java programming language is designed to work on any computer platform (any machine and operating system). The program could be used with students in web-based instruction or in a computer laboratory setting; it may also be of use in some research or outreach applications. While SIP is similar to other image processing programs, it is unique in some important respects. For example, SIP can load images from the user's machine or from the Web. An instructor can put images on a web server for students to load and analyze on their own personal computer. Or, the instructor can inform the students of images to load from any other web server. Furthermore, since SIP was written with students in mind, the philosophy is to present the user with the most basic tools necessary to process and analyze astronomical images. Images can be combined (by addition, subtraction, multiplication, or division), multiplied by a constant, smoothed, cropped, flipped, rotated, and so on. Statistics can be gathered for pixels within a box drawn by the user. Basic tools are available for gathering data from an image which can be used for performing simple differential photometry, or astrometry. Therefore, students can learn how astronomical image processing works. Since SIP is not part of a commercial CCD camera package, the program is written to handle the most common denominator image file, the FITS format.

  20. Image Based Solution to Occlusion Problem for Multiple Robots Navigation

    Directory of Open Access Journals (Sweden)

    Taj Mohammad Khan

    2012-04-01

    Full Text Available In machine vision, occlusions problem is always a challenging issue in image based mapping and navigation tasks. This paper presents a multiple view vision based algorithm for the development of occlusion-free map of the indoor environment. The map is assumed to be utilized by the mobile robots within the workspace. It has wide range of applications, including mobile robot path planning and navigation, access control in restricted areas, and surveillance systems. We used wall mounted fixed camera system. After intensity adjustment and background subtraction of the synchronously captured images, the image registration was performed. We applied our algorithm on the registered images to resolve the occlusion problem. This technique works well even in the existence of total occlusion for a longer period.

  1. Optimization of an Image-Based Talking Head System

    Directory of Open Access Journals (Sweden)

    Kang Liu

    2009-01-01

    Full Text Available This paper presents an image-based talking head system, which includes two parts: analysis and synthesis. The audiovisual analysis part creates a face model of a recorded human subject, which is composed of a personalized 3D mask as well as a large database of mouth images and their related information. The synthesis part generates natural looking facial animations from phonetic transcripts of text. A critical issue of the synthesis is the unit selection which selects and concatenates these appropriate mouth images from the database such that they match the spoken words of the talking head. Selection is based on lip synchronization and the similarity of consecutive images. The unit selection is refined in this paper, and Pareto optimization is used to train the unit selection. Experimental results of subjective tests show that most people cannot distinguish our facial animations from real videos.

  2. Image segmentation algorithm based on T-junctions cues

    Science.gov (United States)

    Qian, Yanyu; Cao, Fengyun; Wang, Lu; Yang, Xuejie

    2016-03-01

    To improve the over-segmentation and over-merge phenomenon of single image segmentation algorithm,a novel approach of combing Graph-Based algorithm and T-junctions cues is proposed in this paper. First, a method by L0 gradient minimization is applied to the smoothing of the target image eliminate artifacts caused by noise and texture detail; Then, the initial over-segmentation result of the smoothing image using the graph-based algorithm; Finally, the final results via a region fusion strategy by t-junction cues. Experimental results on a variety of images verify the new approach's efficiency in eliminating artifacts caused by noise,segmentation accuracy and time complexity has been significantly improved.

  3. Image annotation based on positive-negative instances learning

    Science.gov (United States)

    Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

    2017-07-01

    Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

  4. Initial Investigation of Software-Based Bone-Suppressed Imaging

    International Nuclear Information System (INIS)

    Park, Eunpyeong; Youn, Hanbean; Kim, Ho Kyung

    2015-01-01

    Chest radiography is the most widely used imaging modality in medicine. However, the diagnostic performance of chest radiography is deteriorated by the anatomical background of the patient. So, dual energy imaging (DEI) has recently been emerged and demonstrated an improved. However, the typical DEI requires more than two projections, hence causing additional patient dose. The motion artifact is another concern in the DEI. In this study, we investigate DEI-like bone-suppressed imaging based on the post processing of a single radiograph. To obtain bone-only images, we use the artificial neural network (ANN) method with the error backpropagation-based machine learning approach. The computational load of learning process of the ANN is too heavy for a practical implementation because we use the gradient descent method for the error backpropagation. We will use a more advanced error propagation method for the learning process

  5. Prospective regularization design in prior-image-based reconstruction

    International Nuclear Information System (INIS)

    Dang, Hao; Siewerdsen, Jeffrey H; Stayman, J Webster

    2015-01-01

    Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in

  6. Region-Based Color Image Indexing and Retrieval

    DEFF Research Database (Denmark)

    Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

    2001-01-01

    In this paper a region-based color image indexing and retrieval algorithm is presented. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of the regions. A new color distance is also defined for this algorithm. Based on ....... Experimental results demonstrate the performance of the algorithm. The development of an intelligent image content-based search engine for the World Wide Web is also presented, as a direct application of the presented algorithm....

  7. Imaging of the skull base anatomy; Schnittbildanatomie der Schaedelbasis

    Energy Technology Data Exchange (ETDEWEB)

    Wuest, Wolfgang; Uder, Michael; Lell, Michael [Erlangen-Nuernberg Univ., Universitaetsklinikum (Germany). Radiologisches Institut

    2016-09-15

    The skull base divides the extracranial from the intracranial compartment and contains a multiplicity of bony and soft tissue structures. For evaluating the skull base profound knowledge of the complex anatomy is mandatory. To limit the number of differential diagnosis it is important to be familiar with the contents of the different compartments. Due to the technical progress and the difficulty in assessing the skull base clinically imaging plays a significant role in diagnosis. For imaging both MRI and CT are used, which represent not competing but complementary methods.

  8. Photonics-Based Microwave Image-Reject Mixer

    Directory of Open Access Journals (Sweden)

    Dan Zhu

    2018-03-01

    Full Text Available Recent developments in photonics-based microwave image-reject mixers (IRMs are reviewed with an emphasis on the pre-filtering method, which applies an optical or electrical filter to remove the undesired image, and the phase cancellation method, which is realized by introducing an additional phase to the converted image and cancelling it through coherent combination without phase shift. Applications of photonics-based microwave IRM in electronic warfare, radar systems and satellite payloads are described. The inherent challenges of implementing photonics-based microwave IRM to meet specific requirements of the radio frequency (RF system are discussed. Developmental trends of the photonics-based microwave IRM are also discussed.

  9. Content-Based Image Retrieval Based on Electromagnetism-Like Mechanism

    Directory of Open Access Journals (Sweden)

    Hamid A. Jalab

    2013-01-01

    Full Text Available Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper presents a novel algorithm for increasing the precision in content-based image retrieval based on electromagnetism optimization technique. The electromagnetism optimization is a nature-inspired technique that follows the collective attraction-repulsion mechanism by considering each image as an electrical charge. The algorithm is composed of two phases: fitness function measurement and electromagnetism optimization technique. It is implemented on a database with 8,000 images spread across 80 classes with 100 images in each class. Eight thousand queries are fired on the database, and the overall average precision is computed. Experimental results of the proposed approach have shown significant improvement in the retrieval performance in regard to precision.

  10. IMAGE SEGMENTATION BASED ON MARKOV RANDOM FIELD AND WATERSHED TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    This paper presented a method that incorporates Markov Random Field(MRF), watershed segmentation and merging techniques for performing image segmentation and edge detection tasks. MRF is used to obtain an initial estimate of x regions in the image under process where in MRF model, gray level x, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The process needs an initial segmented result. An initial segmentation is got based on K-means clustering technique and the minimum distance, then the region process in modeled by MRF to obtain an image contains different intensity regions. Starting from this we calculate the gradient values of that image and then employ a watershed technique. When using MRF method it obtains an image that has different intensity regions and has all the edge and region information, then it improves the segmentation result by superimpose closed and an accurate boundary of each region using watershed algorithm. After all pixels of the segmented regions have been processed, a map of primitive region with edges is generated. Finally, a merge process based on averaged mean values is employed. The final segmentation and edge detection result is one closed boundary per actual region in the image.

  11. Research of second harmonic generation images based on texture analysis

    Science.gov (United States)

    Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

    2014-09-01

    Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

  12. A Wildlife Monitoring System Based on Wireless Image Sensor Networks

    Directory of Open Access Journals (Sweden)

    Junguo Zhang

    2014-10-01

    Full Text Available Survival and development of wildlife sustains the balance and stability of the entire ecosystem. Wildlife monitoring can provide lots of information such as wildlife species, quantity, habits, quality of life and habitat conditions, to help researchers grasp the status and dynamics of wildlife resources, and to provide basis for the effective protection, sustainable use, and scientific management of wildlife resources. Wildlife monitoring is the foundation of wildlife protection and management. Wireless Sensor Networks (WSN technology has become the most popular technology in the field of information. With advance of the CMOS image sensor technology, wireless sensor networks combined with image sensors, namely Wireless Image Sensor Networks (WISN technology, has emerged as an alternative in monitoring applications. Monitoring wildlife is one of its most promising applications. In this paper, system architecture of the wildlife monitoring system based on the wireless image sensor networks was presented to overcome the shortcomings of the traditional monitoring methods. Specifically, some key issues including design of wireless image sensor nodes and software process design have been studied and presented. A self-powered rotatable wireless infrared image sensor node based on ARM and an aggregation node designed for large amounts of data were developed. In addition, their corresponding software was designed. The proposed system is able to monitor wildlife accurately, automatically, and remotely in all-weather condition, which lays foundations for applications of wireless image sensor networks in wildlife monitoring.

  13. [Research on Spectral Polarization Imaging System Based on Static Modulation].

    Science.gov (United States)

    Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

    2015-04-01

    The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

  14. Cnn Based Retinal Image Upscaling Using Zero Component Analysis

    Science.gov (United States)

    Nasonov, A.; Chesnakov, K.; Krylov, A.

    2017-05-01

    The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

  15. A UNIX-based prototype biomedical virtual image processor

    International Nuclear Information System (INIS)

    Fahy, J.B.; Kim, Y.

    1987-01-01

    The authors have developed a multiprocess virtual image processor for the IBM PC/AT, in order to maximize image processing software portability for biomedical applications. An interprocess communication scheme, based on two-way metacode exchange, has been developed and verified for this purpose. Application programs call a device-independent image processing library, which transfers commands over a shared data bridge to one or more Autonomous Virtual Image Processors (AVIP). Each AVIP runs as a separate process in the UNIX operating system, and implements the device-independent functions on the image processor to which it corresponds. Application programs can control multiple image processors at a time, change the image processor configuration used at any time, and are completely portable among image processors for which an AVIP has been implemented. Run-time speeds have been found to be acceptable for higher level functions, although rather slow for lower level functions, owing to the overhead associated with sending commands and data over the shared data bridge

  16. Advanced Contrast Agents for Multimodal Biomedical Imaging Based on Nanotechnology.

    Science.gov (United States)

    Calle, Daniel; Ballesteros, Paloma; Cerdán, Sebastián

    2018-01-01

    Clinical imaging modalities have reached a prominent role in medical diagnosis and patient management in the last decades. Different image methodologies as Positron Emission Tomography, Single Photon Emission Tomography, X-Rays, or Magnetic Resonance Imaging are in continuous evolution to satisfy the increasing demands of current medical diagnosis. Progress in these methodologies has been favored by the parallel development of increasingly more powerful contrast agents. These are molecules that enhance the intrinsic contrast of the images in the tissues where they accumulate, revealing noninvasively the presence of characteristic molecular targets or differential physiopathological microenvironments. The contrast agent field is currently moving to improve the performance of these molecules by incorporating the advantages that modern nanotechnology offers. These include, mainly, the possibilities to combine imaging and therapeutic capabilities over the same theranostic platform or improve the targeting efficiency in vivo by molecular engineering of the nanostructures. In this review, we provide an introduction to multimodal imaging methods in biomedicine, the sub-nanometric imaging agents previously used and the development of advanced multimodal and theranostic imaging agents based in nanotechnology. We conclude providing some illustrative examples from our own laboratories, including recent progress in theranostic formulations of magnetoliposomes containing ω-3 poly-unsaturated fatty acids to treat inflammatory diseases, or the use of stealth liposomes engineered with a pH-sensitive nanovalve to release their cargo specifically in the acidic extracellular pH microenvironment of tumors.

  17. Optical 3D watermark based digital image watermarking for telemedicine

    Science.gov (United States)

    Li, Xiao Wei; Kim, Seok Tae

    2013-12-01

    Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.

  18. Decision making based on emotional images

    Directory of Open Access Journals (Sweden)

    Kentaro eKatahira

    2011-10-01

    Full Text Available The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the reward value of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants’ choice data, we used reinforcement learning models that have success- fully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

  19. Knowledge-based interpretation of cranial MR images

    International Nuclear Information System (INIS)

    Kuhn, M.H.; Menhardt, W.; Schmidt, K.H.

    1987-01-01

    A computerized system is described that can be used to evaluate an MR tomogram automatically to support clinical identification of anatomic and pathologic structures and to aid in planning MR measurements. Knowledge from three domains is used for the interpretation of an MR image: nosologic knowledge, knowledge of MR imaging parameters, and anatomic and morphologic knowledge. Nosologic information is used to generate hypotheses about possible pathologies and their locations, based on the signs and symptoms of the patient. With this information, a sequence of interpretation modules, each able to detect substructures in already detected structures with the aid of techniques from image processing, pattern recognition, and artificial intelligence, is generated and executed

  20. A Reliable Image Watermarking Scheme Based on Redistributed Image Normalization and SVD

    Directory of Open Access Journals (Sweden)

    Musrrat Ali

    2016-01-01

    Full Text Available Digital image watermarking is the process of concealing secret information in a digital image for protecting its rightful ownership. Most of the existing block based singular value decomposition (SVD digital watermarking schemes are not robust to geometric distortions, such as rotation in an integer multiple of ninety degree and image flipping, which change the locations of the pixels but don’t make any changes to the pixel’s intensity of the image. Also, the schemes have used a constant scaling factor to give the same weightage to the coefficients of different magnitudes that results in visible distortion in some regions of the watermarked image. Therefore, to overcome the problems mentioned here, this paper proposes a novel image watermarking scheme by incorporating the concepts of redistributed image normalization and variable scaling factor depending on the coefficient’s magnitude to be embedded. Furthermore, to enhance the security and robustness the watermark is shuffled by using the piecewise linear chaotic map before the embedding. To investigate the robustness of the scheme several attacks are applied to seriously distort the watermarked image. Empirical analysis of the results has demonstrated the efficiency of the proposed scheme.

  1. Fast image acquisition and processing on a TV camera-based portal imaging system

    International Nuclear Information System (INIS)

    Baier, K.; Meyer, J.

    2005-01-01

    The present paper describes the fast acquisition and processing of portal images directly from a TV camera-based portal imaging device (Siemens Beamview Plus trademark). This approach employs not only hard- and software included in the standard package installed by the manufacturer (in particular the frame grabber card and the Matrox(tm) Intellicam interpreter software), but also a software tool developed in-house for further processing and analysis of the images. The technical details are presented, including the source code for the Matrox trademark interpreter script that enables the image capturing process. With this method it is possible to obtain raw images directly from the frame grabber card at an acquisition rate of 15 images per second. The original configuration by the manufacturer allows the acquisition of only a few images over the course of a treatment session. The approach has a wide range of applications, such as quality assurance (QA) of the radiation beam, real-time imaging, real-time verification of intensity-modulated radiation therapy (IMRT) fields, and generation of movies of the radiation field (fluoroscopy mode). (orig.)

  2. Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

    International Nuclear Information System (INIS)

    Zhou Xiaolin; Yun Mingkai; Cao Xuexiang; Liu Shuangquan; Wang Lu; Huang Xianchao; Wei Long

    2014-01-01

    Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose. (authors)

  3. Content-based image retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  4. Content-Based Image Retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  5. Optical double-image cryptography based on diffractive imaging with a laterally-translated phase grating.

    Science.gov (United States)

    Chen, Wen; Chen, Xudong; Sheppard, Colin J R

    2011-10-10

    In this paper, we propose a method using structured-illumination-based diffractive imaging with a laterally-translated phase grating for optical double-image cryptography. An optical cryptosystem is designed, and multiple random phase-only masks are placed in the optical path. When a phase grating is laterally translated just before the plaintexts, several diffraction intensity patterns (i.e., ciphertexts) can be correspondingly obtained. During image decryption, an iterative retrieval algorithm is developed to extract plaintexts from the ciphertexts. In addition, security and advantages of the proposed method are analyzed. Feasibility and effectiveness of the proposed method are demonstrated by numerical simulation results. © 2011 Optical Society of America

  6. An Image Registration Based Technique for Noninvasive Vascular Elastography

    OpenAIRE

    Valizadeh, Sina; Makkiabadi, Bahador; Mirbagheri, Alireza; Soozande, Mehdi; Manwar, Rayyan; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza

    2018-01-01

    Non-invasive vascular elastography is an emerging technique in vascular tissue imaging. During the past decades, several techniques have been suggested to estimate the tissue elasticity by measuring the displacement of the Carotid vessel wall. Cross correlation-based methods are the most prevalent approaches to measure the strain exerted in the wall vessel by the blood pressure. In the case of a low pressure, the displacement is too small to be apparent in ultrasound imaging, especially in th...

  7. Image Segmentation Based on Period Difference of the Oscillation

    Institute of Scientific and Technical Information of China (English)

    王直杰; 张珏; 范宏; 柯克峰

    2004-01-01

    A new method for image segmentation based on pulse neural network is proposed. Every neuron in the network represents one pixel in the image and the network is locally connected.Each group of the neurons that correspond to each object synchronizes while different gronps of the neurons oscillate at different period. Applying this period difference,different objects are divided. In addition to simulation, an analysis of the mechanism of the method is presented in this paper.

  8. Near-field acoustic imaging based on Laplacian sparsity

    DEFF Research Database (Denmark)

    Fernandez Grande, Efren; Daudet, Laurent

    2016-01-01

    We present a sound source identification method for near-field acoustic imaging of extended sources. The methodology is based on a wave superposition method (or equivalent source method) that promotes solutions with sparse higher order spatial derivatives. Instead of promoting direct sparsity......, and the validity of the wave extrapolation used for the reconstruction is examined. It is shown that this methodology can overcome conventional limits of spatial sampling, and is therefore valid for wide-band acoustic imaging of extended sources....

  9. Ontology-Based Knowledge Organization for the Radiograph Images Segmentation

    Directory of Open Access Journals (Sweden)

    MATEI, O.

    2008-04-01

    Full Text Available The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.

  10. Effects of extraocular muscle surgery in children with monocular blindness and bilateral nystagmus.

    Science.gov (United States)

    Sturm, Veit; Hejcmanova, Marketa; Landau, Klara

    2014-11-20

    Monocular infantile blindness may be associated with bilateral horizontal nystagmus, a subtype of fusion maldevelopment nystagmus syndrome (FMNS). Patients often adopt a significant anomalous head posture (AHP) towards the fixing eye in order to dampen the nystagmus. This clinical entity has also been reported as unilateral Ciancia syndrome. The aim of the study was to ascertain the clinical features and surgical outcome of patients with FMNS with infantile unilateral visual loss. In this retrospective case series, nine consecutive patients with FMNS with infantile unilateral visual loss underwent strabismus surgery to correct an AHP and/or improve ocular alignment. Outcome measures included amount of AHP and deviation at last follow-up. Eye muscle surgery according to the principles of Kestenbaum resulted in a marked reduction or elimination of the AHP. On average, a reduction of AHP of 1.3°/mm was achieved by predominantly performing combined horizontal recess-resect surgery in the intact eye. In cases of existing esotropia (ET) this procedure also markedly reduced the angle of deviation. A dosage calculation of 3 prism diopters/mm was established. We advocate a tailored surgical approach in FMNS with infantile unilateral visual loss. In typical patients who adopt a significant AHP accompanied by a large ET, we suggest an initial combined recess-resect surgery in the intact eye. This procedure regularly led to a marked reduction of the head turn and ET. In patients without significant strabismus, a full Kestenbaum procedure was successful, while ET in a patient with a minor AHP was corrected by performing a bimedial recession.

  11. Visual system plasticity in mammals: the story of monocular enucleation-induced vision loss

    Science.gov (United States)

    Nys, Julie; Scheyltjens, Isabelle; Arckens, Lutgarde

    2015-01-01

    The groundbreaking work of Hubel and Wiesel in the 1960’s on ocular dominance plasticity instigated many studies of the visual system of mammals, enriching our understanding of how the development of its structure and function depends on high quality visual input through both eyes. These studies have mainly employed lid suturing, dark rearing and eye patching applied to different species to reduce or impair visual input, and have created extensive knowledge on binocular vision. However, not all aspects and types of plasticity in the visual cortex have been covered in full detail. In that regard, a more drastic deprivation method like enucleation, leading to complete vision loss appears useful as it has more widespread effects on the afferent visual pathway and even on non-visual brain regions. One-eyed vision due to monocular enucleation (ME) profoundly affects the contralateral retinorecipient subcortical and cortical structures thereby creating a powerful means to investigate cortical plasticity phenomena in which binocular competition has no vote.In this review, we will present current knowledge about the specific application of ME as an experimental tool to study visual and cross-modal brain plasticity and compare early postnatal stages up into adulthood. The structural and physiological consequences of this type of extensive sensory loss as documented and studied in several animal species and human patients will be discussed. We will summarize how ME studies have been instrumental to our current understanding of the differentiation of sensory systems and how the structure and function of cortical circuits in mammals are shaped in response to such an extensive alteration in experience. In conclusion, we will highlight future perspectives and the clinical relevance of adding ME to the list of more longstanding deprivation models in visual system research. PMID:25972788

  12. Monocular and binocular development in children with albinism, infantile nystagmus syndrome, and normal vision.

    Science.gov (United States)

    Huurneman, Bianca; Boonstra, F Nienke

    2013-12-01

    To compare interocular acuity differences, crowding ratios, and binocular summation ratios in 4- to 8-year-old children with albinism (n = 16), children with infantile nystagmus syndrome (n = 10), and children with normal vision (n = 72). Interocular acuity differences and binocular summation ratios were compared between groups. Crowding ratios were calculated by dividing the single Landolt C decimal acuity with the crowded Landolt C decimal acuity mono- and binocularly. A linear regression analysis was conducted to investigate the contribution of 5 predictors to the monocular and binocular crowding ratio: nystagmus amplitude, nystagmus frequency, strabismus, astigmatism, and anisometropia. Crowding ratios were higher under mono- and binocular viewing conditions for children with infantile nystagmus syndrome than for children with normal vision. Children with albinism showed higher crowding ratios in their poorer eye and under binocular viewing conditions than children with normal vision. Children with albinism and children with infantile nystagmus syndrome showed larger interocular acuity differences than children with normal vision (0.1 logMAR in our clinical groups and 0.0 logMAR in children with normal vision). Binocular summation ratios did not differ between groups. Strabismus and nystagmus amplitude predicted the crowding ratio in the poorer eye (p = 0.015 and p = 0.005, respectively). The crowding ratio in the better eye showed a marginally significant relation with nystagmus frequency and depth of anisometropia (p = 0.082 and p = 0.070, respectively). The binocular crowding ratio was not predicted by any of the variables. Children with albinism and children with infantile nystagmus syndrome show larger interocular acuity differences than children with normal vision. Strabismus and nystagmus amplitude are significant predictors of the crowding ratio in the poorer eye.

  13. Optical colour image watermarking based on phase-truncated linear canonical transform and image decomposition

    Science.gov (United States)

    Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun

    2018-05-01

    This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.

  14. Application of content-based image compression to telepathology

    Science.gov (United States)

    Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

    2002-05-01

    Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

  15. Shape-based grey-level image interpolation

    International Nuclear Information System (INIS)

    Keh-Shih Chuang; Chun-Yuan Chen; Ching-Kai Yeh

    1999-01-01

    The three-dimensional (3D) object data obtained from a CT scanner usually have unequal sampling frequencies in the x-, y- and z-directions. Generally, the 3D data are first interpolated between slices to obtain isotropic resolution, reconstructed, then operated on using object extraction and display algorithms. The traditional grey-level interpolation introduces a layer of intermediate substance and is not suitable for objects that are very different from the opposite background. The shape-based interpolation method transfers a pixel location to a parameter related to the object shape and the interpolation is performed on that parameter. This process is able to achieve a better interpolation but its application is limited to binary images only. In this paper, we present an improved shape-based interpolation method for grey-level images. The new method uses a polygon to approximate the object shape and performs the interpolation using polygon vertices as references. The binary images representing the shape of the object were first generated via image segmentation on the source images. The target object binary image was then created using regular shape-based interpolation. The polygon enclosing the object for each slice can be generated from the shape of that slice. We determined the relative location in the source slices of each pixel inside the target polygon using the vertices of a polygon as the reference. The target slice grey-level was interpolated from the corresponding source image pixels. The image quality of this interpolation method is better and the mean squared difference is smaller than with traditional grey-level interpolation. (author)

  16. Validation of Diagnostic Imaging Based on Repeat Examinations. An Image Interpretation Model

    International Nuclear Information System (INIS)

    Isberg, B.; Jorulf, H.; Thorstensen, Oe.

    2004-01-01

    Purpose: To develop an interpretation model, based on repeatedly acquired images, aimed at improving assessments of technical efficacy and diagnostic accuracy in the detection of small lesions. Material and Methods: A theoretical model is proposed. The studied population consists of subjects that develop focal lesions which increase in size in organs of interest during the study period. The imaging modality produces images that can be re-interpreted with high precision, e.g. conventional radiography, computed tomography, and magnetic resonance imaging. At least four repeat examinations are carried out. Results: The interpretation is performed in four or five steps: 1. Independent readers interpret the examinations chronologically without access to previous or subsequent films. 2. Lesions found on images at the last examination are included in the analysis, with interpretation in consensus. 3. By concurrent back-reading in consensus, the lesions are identified on previous images until they are so small that even in retrospect they are undetectable. The earliest examination at which included lesions appear is recorded, and the lesions are verified by their growth (imaging reference standard). Lesion size and other characteristics may be recorded. 4. Records made at step 1 are corrected to those of steps 2 and 3. False positives are recorded. 5. (Optional) Lesion type is confirmed by another diagnostic test. Conclusion: Applied on subjects with progressive disease, the proposed image interpretation model may improve assessments of technical efficacy and diagnostic accuracy in the detection of small focal lesions. The model may provide an accurate imaging reference standard as well as repeated detection rates and false-positive rates for tested imaging modalities. However, potential review bias necessitates a strict protocol

  17. Using a web-based image quality assurance reporting system to improve image quality.

    Science.gov (United States)

    Czuczman, Gregory J; Pomerantz, Stuart R; Alkasab, Tarik K; Huang, Ambrose J

    2013-08-01

    The purpose of this study is to show the impact of a web-based image quality assurance reporting system on the rates of three common image quality errors at our institution. A web-based image quality assurance reporting system was developed and used beginning in April 2009. Image quality endpoints were assessed immediately before deployment (period 1), approximately 18 months after deployment of a prototype reporting system (period 2), and approximately 12 months after deployment of a subsequent upgraded department-wide reporting system (period 3). A total of 3067 axillary shoulder radiographs were reviewed for correct orientation, 355 shoulder CT scans were reviewed for correct reformatting of coronal and sagittal images, and 346 sacral MRI scans were reviewed for correct acquisition plane of axial images. Error rates for each review period were calculated and compared using the Fisher exact test. Error rates of axillary shoulder radiograph orientation were 35.9%, 7.2%, and 10.0%, respectively, for the three review periods. The decrease in error rate between periods 1 and 2 was statistically significant (p < 0.0001). Error rates of shoulder CT reformats were 9.8%, 2.7%, and 5.8%, respectively, for the three review periods. The decrease in error rate between periods 1 and 2 was statistically significant (p = 0.03). Error rates for sacral MRI axial sequences were 96.5%, 32.5%, and 3.4%, respectively, for the three review periods. The decrease in error rates between periods 1 and 2 and between periods 2 and 3 was statistically significant (p < 0.0001). A web-based system for reporting image quality errors may be effective for improving image quality.

  18. Physics-based deformable organisms for medical image analysis

    Science.gov (United States)

    Hamarneh, Ghassan; McIntosh, Chris

    2005-04-01

    Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

  19. Image Relaxation Matching Based on Feature Points for DSM Generation

    Institute of Scientific and Technical Information of China (English)

    ZHENG Shunyi; ZHANG Zuxun; ZHANG Jianqing

    2004-01-01

    In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlaton matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.

  20. Target Identification Using Harmonic Wavelet Based ISAR Imaging

    Science.gov (United States)

    Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

    2006-12-01

    A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

  1. Radionuclide-Based Cancer Imaging Targeting the Carcinoembryonic Antigen

    Directory of Open Access Journals (Sweden)

    Hao Hong

    2008-01-01

    Full Text Available Carcinoembryonic antigen (CEA, highly expressed in many cancer types, is an important target for cancer diagnosis and therapy. Radionuclide-based imaging techniques (gamma camera, single photon emission computed tomography [SPECT] and positron emission tomography [PET] have been extensively explored for CEA-targeted cancer imaging both preclinically and clinically. Briefly, these studies can be divided into three major categories: antibody-based, antibody fragment-based and pretargeted imaging. Radiolabeled anti-CEA antibodies, reported the earliest among the three categories, typically gave suboptimal tumor contrast due to the prolonged circulation life time of intact antibodies. Subsequently, a number of engineered anti-CEA antibody fragments (e.g. Fab’, scFv, minibody, diabody and scFv-Fc have been labeled with a variety of radioisotopes for CEA imaging, many of which have entered clinical investigation. CEA-Scan (a 99mTc-labeled anti-CEA Fab’ fragment has already been approved by the United States Food and Drug Administration for cancer imaging. Meanwhile, pretargeting strategies have also been developed for CEA imaging which can give much better tumor contrast than the other two methods, if the system is designed properly. In this review article, we will summarize the current state-of-the-art of radionuclide-based cancer imaging targeting CEA. Generally, isotopes with short half-lives (e.g. 18F and 99mTc are more suitable for labeling small engineered antibody fragments while the isotopes with longer half-lives (e.g. 123I and 111In are needed for antibody labeling to match its relatively long circulation half-life. With further improvement in tumor targeting efficacy and radiolabeling strategies, novel CEA-targeted agents may play an important role in cancer patient management, paving the way to “personalized medicine”.

  2. Image based 3D city modeling : Comparative study

    Directory of Open Access Journals (Sweden)

    S. P. Singh

    2014-06-01

    Full Text Available 3D city model is a digital representation of the Earth’s surface and it’s related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India. This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can’t do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good

  3. Comparing Four Touch-Based Interaction Techniques for an Image-Based Audience Response System

    NARCIS (Netherlands)

    Jorritsma, Wiard; Prins, Jonatan T.; van Ooijen, Peter M. A.

    2015-01-01

    This study aimed to determine the most appropriate touch-based interaction technique for I2Vote, an image-based audience response system for radiology education in which users need to accurately mark a target on a medical image. Four plausible techniques were identified: land-on, take-off,

  4. Cardiovascular imaging environment: will the future be cloud-based?

    Science.gov (United States)

    Kawel-Boehm, Nadine; Bluemke, David A

    2017-07-01

    In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

  5. Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

    Science.gov (United States)

    Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

    2014-12-01

    Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on

  6. Integrated optical 3D digital imaging based on DSP scheme

    Science.gov (United States)

    Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.

    2008-03-01

    We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.

  7. Facial Image Compression Based on Structured Codebooks in Overcomplete Domain

    Directory of Open Access Journals (Sweden)

    Vila-Forcén JE

    2006-01-01

    Full Text Available We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.

  8. Digital Image Encryption Algorithm Design Based on Genetic Hyperchaos

    Directory of Open Access Journals (Sweden)

    Jian Wang

    2016-01-01

    Full Text Available In view of the present chaotic image encryption algorithm based on scrambling (diffusion is vulnerable to choosing plaintext (ciphertext attack in the process of pixel position scrambling, we put forward a image encryption algorithm based on genetic super chaotic system. The algorithm, by introducing clear feedback to the process of scrambling, makes the scrambling effect related to the initial chaos sequence and the clear text itself; it has realized the image features and the organic fusion of encryption algorithm. By introduction in the process of diffusion to encrypt plaintext feedback mechanism, it improves sensitivity of plaintext, algorithm selection plaintext, and ciphertext attack resistance. At the same time, it also makes full use of the characteristics of image information. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist plaintext (ciphertext attack, statistical attack, and information entropy attack but also effectively improve the efficiency of image encryption, which is a relatively secure and effective way of image communication.

  9. A general framework for regularized, similarity-based image restoration.

    Science.gov (United States)

    Kheradmand, Amin; Milanfar, Peyman

    2014-12-01

    Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

  10. Optical image encryption method based on incoherent imaging and polarized light encoding

    Science.gov (United States)

    Wang, Q.; Xiong, D.; Alfalou, A.; Brosseau, C.

    2018-05-01

    We propose an incoherent encoding system for image encryption based on a polarized encoding method combined with an incoherent imaging. Incoherent imaging is the core component of this proposal, in which the incoherent point-spread function (PSF) of the imaging system serves as the main key to encode the input intensity distribution thanks to a convolution operation. An array of retarders and polarizers is placed on the input plane of the imaging structure to encrypt the polarized state of light based on Mueller polarization calculus. The proposal makes full use of randomness of polarization parameters and incoherent PSF so that a multidimensional key space is generated to deal with illegal attacks. Mueller polarization calculus and incoherent illumination of imaging structure ensure that only intensity information is manipulated. Another key advantage is that complicated processing and recording related to a complex-valued signal are avoided. The encoded information is just an intensity distribution, which is advantageous for data storage and transition because information expansion accompanying conventional encryption methods is also avoided. The decryption procedure can be performed digitally or using optoelectronic devices. Numerical simulation tests demonstrate the validity of the proposed scheme.

  11. An Integrative Object-Based Image Analysis Workflow for Uav Images

    Science.gov (United States)

    Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

    2016-06-01

    In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  12. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  13. Improved image registration by sparse patch-based deformation estimation.

    Science.gov (United States)

    Kim, Minjeong; Wu, Guorong; Wang, Qian; Lee, Seong-Whan; Shen, Dinggang

    2015-01-15

    Despite intensive efforts for decades, deformable image registration is still a challenging problem due to the potential large anatomical differences across individual images, which limits the registration performance. Fortunately, this issue could be alleviated if a good initial deformation can be provided for the two images under registration, which are often termed as the moving subject and the fixed template, respectively. In this work, we present a novel patch-based initial deformation prediction framework for improving the performance of existing registration algorithms. Our main idea is to estimate the initial deformation between subject and template in a patch-wise fashion by using the sparse representation technique. We argue that two image patches should follow the same deformation toward the template image if their patch-wise appearance patterns are similar. To this end, our framework consists of two stages, i.e., the training stage and the application stage. In the training stage, we register all training images to the pre-selected template, such that the deformation of each training image with respect to the template is known. In the application stage, we apply the following four steps to efficiently calculate the initial deformation field for the new test subject: (1) We pick a small number of key points in the distinctive regions of the test subject; (2) for each key point, we extract a local patch and form a coupled appearance-deformation dictionary from training images where each dictionary atom consists of the image intensity patch as well as their respective local deformations; (3) a small set of training image patches in the coupled dictionary are selected to represent the image patch of each subject key point by sparse representation. Then, we can predict the initial deformation for each subject key point by propagating the pre-estimated deformations on the selected training patches with the same sparse representation coefficients; and (4) we

  14. Filler segmentation of SEM paper images based on mathematical morphology.

    Science.gov (United States)

    Ait Kbir, M; Benslimane, Rachid; Princi, Elisabetta; Vicini, Silvia; Pedemonte, Enrico

    2007-07-01

    Recent developments in microscopy and image processing have made digital measurements on high-resolution images of fibrous materials possible. This helps to gain a better understanding of the structure and other properties of the material at micro level. In this paper SEM image segmentation based on mathematical morphology is proposed. In fact, paper models images (Whatman, Murillo, Watercolor, Newsprint paper) selected in the context of the Euro Mediterranean PaperTech Project have different distributions of fibers and fillers, caused by the presence of SiAl and CaCO3 particles. It is a microscopy challenge to make filler particles in the sheet distinguishable from the other components of the paper surface. This objectif is reached here by using switable strutural elements and mathematical morphology operators.

  15. Image contrast enhancement based on a local standard deviation model

    International Nuclear Information System (INIS)

    Chang, Dah-Chung; Wu, Wen-Rong

    1996-01-01

    The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt's Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm

  16. Image Compression Based On Wavelet, Polynomial and Quadtree

    Directory of Open Access Journals (Sweden)

    Bushra A. SULTAN

    2011-01-01

    Full Text Available In this paper a simple and fast image compression scheme is proposed, it is based on using wavelet transform to decompose the image signal and then using polynomial approximation to prune the smoothing component of the image band. The architect of proposed coding scheme is high synthetic where the error produced due to polynomial approximation in addition to the detail sub-band data are coded using both quantization and Quadtree spatial coding. As a last stage of the encoding process shift encoding is used as a simple and efficient entropy encoder to compress the outcomes of the previous stage.The test results indicate that the proposed system can produce a promising compression performance while preserving the image quality level.

  17. Image Retrieval Algorithm Based on Discrete Fractional Transforms

    Science.gov (United States)

    Jindal, Neeru; Singh, Kulbir

    2013-06-01

    The discrete fractional transforms is a signal processing tool which suggests computational algorithms and solutions to various sophisticated applications. In this paper, a new technique to retrieve the encrypted and scrambled image based on discrete fractional transforms has been proposed. Two-dimensional image was encrypted using discrete fractional transforms with three fractional orders and two random phase masks placed in the two intermediate planes. The significant feature of discrete fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. Security strength was enhanced (1024!)4 times by scrambling the encrypted image. In decryption process, image retrieval is sensitive for both correct fractional order keys and scrambling algorithm. The proposed approach make the brute force attack infeasible. Mean square error and relative error are the recital parameters to verify validity of proposed method.

  18. Mobile cosmetics advisor: an imaging based mobile service

    Science.gov (United States)

    Bhatti, Nina; Baker, Harlyn; Chao, Hui; Clearwater, Scott; Harville, Mike; Jain, Jhilmil; Lyons, Nic; Marguier, Joanna; Schettino, John; Süsstrunk, Sabine

    2010-01-01

    Selecting cosmetics requires visual information and often benefits from the assessments of a cosmetics expert. In this paper we present a unique mobile imaging application that enables women to use their cell phones to get immediate expert advice when selecting personal cosmetic products. We derive the visual information from analysis of camera phone images, and provide the judgment of the cosmetics specialist through use of an expert system. The result is a new paradigm for mobile interactions-image-based information services exploiting the ubiquity of camera phones. The application is designed to work with any handset over any cellular carrier using commonly available MMS and SMS features. Targeted at the unsophisticated consumer, it must be quick and easy to use, not requiring download capabilities or preplanning. Thus, all application processing occurs in the back-end system and not on the handset itself. We present the imaging pipeline technology and a comparison of the services' accuracy with respect to human experts.

  19. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  20. Multi scales based sparse matrix spectral clustering image segmentation

    Science.gov (United States)

    Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

    2018-04-01

    In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

  1. Color image encryption based on Coupled Nonlinear Chaotic Map

    International Nuclear Information System (INIS)

    Mazloom, Sahar; Eftekhari-Moghadam, Amir Masud

    2009-01-01

    Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional methods. The desirable cryptographic properties of the chaotic maps such as sensitivity to initial conditions and random-like behavior have attracted the attention of cryptographers to develop new encryption algorithms. Therefore, recent researches of image encryption algorithms have been increasingly based on chaotic systems, though the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper proposes a Coupled Nonlinear Chaotic Map, called CNCM, and a novel chaos-based image encryption algorithm to encrypt color images by using CNCM. The chaotic cryptography technique which used in this paper is a symmetric key cryptography with a stream cipher structure. In order to increase the security of the proposed algorithm, 240 bit-long secret key is used to generate the initial conditions and parameters of the chaotic map by making some algebraic transformations to the key. These transformations as well as the nonlinearity and coupling structure of the CNCM have enhanced the cryptosystem security. For getting higher security and higher complexity, the current paper employs the image size and color components to cryptosystem, thereby significantly increasing the resistance to known/chosen-plaintext attacks. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for real-time image encryption and transmission.

  2. Research of image retrieval technology based on color feature

    Science.gov (United States)

    Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

    2009-10-01

    Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

  3. ImageGrouper: a group-oriented user interface for content-based image retrieval and digital image arrangement

    NARCIS (Netherlands)

    Nakazato, Munehiro; Manola, L.; Huang, Thomas S.

    In content-based image retrieval (CBIR), experimental (trial-and-error) query with relevance feedback is essential for successful retrieval. Unfortunately, the traditional user interfaces are not suitable for trying different combinations of query examples. This is because first, these systems

  4. Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging

    Directory of Open Access Journals (Sweden)

    Shuanghui Zhang

    2016-04-01

    Full Text Available This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP estimation and the maximum likelihood estimation (MLE are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.

  5. LDPC and SHA based iris recognition for image authentication

    Directory of Open Access Journals (Sweden)

    K. Seetharaman

    2012-11-01

    Full Text Available We introduce a novel way to authenticate an image using Low Density Parity Check (LDPC and Secure Hash Algorithm (SHA based iris recognition method with reversible watermarking scheme, which is based on Integer Wavelet Transform (IWT and threshold embedding technique. The parity checks and parity matrix of LDPC encoding and cancellable biometrics i.e., hash string of unique iris code from SHA-512 are embedded into an image for authentication purpose using reversible watermarking scheme based on IWT and threshold embedding technique. Simply by reversing the embedding process, the original image, parity checks, parity matrix and SHA-512 hash are extracted back from watermarked-image. For authentication, the new hash string produced by employing SHA-512 on error corrected iris code from live person is compared with hash string extracted from watermarked-image. The LDPC code reduces the hamming distance for genuine comparisons by a larger amount than for the impostor comparisons. This results in better separation between genuine and impostor users which improves the authentication performance. Security of this scheme is very high due to the security complexity of SHA-512, which is 2256 under birthday attack. Experimental results show that this approach can assure more accurate authentication with a low false rejection or false acceptance rate and outperforms the prior arts in terms of PSNR.

  6. Biased discriminant euclidean embedding for content-based image retrieval.

    Science.gov (United States)

    Bian, Wei; Tao, Dacheng

    2010-02-01

    With many potential multimedia applications, content-based image retrieval (CBIR) has recently gained more attention for image management and web search. A wide variety of relevance feedback (RF) algorithms have been developed in recent years to improve the performance of CBIR systems. These RF algorithms capture user's preferences and bridge the semantic gap. However, there is still a big room to further the RF performance, because the popular RF algorithms ignore the manifold structure of image low-level visual features. In this paper, we propose the biased discriminative Euclidean embedding (BDEE) which parameterises samples in the original high-dimensional ambient space to discover the intrinsic coordinate of image low-level visual features. BDEE precisely models both the intraclass geometry and interclass discrimination and never meets the undersampled problem. To consider unlabelled samples, a manifold regularization-based item is introduced and combined with BDEE to form the semi-supervised BDEE, or semi-BDEE for short. To justify the effectiveness of the proposed BDEE and semi-BDEE, we compare them against the conventional RF algorithms and show a significant improvement in terms of accuracy and stability based on a subset of the Corel image gallery.

  7. Image based Monte Carlo modeling for computational phantom

    International Nuclear Information System (INIS)

    Cheng, M.; Wang, W.; Zhao, K.; Fan, Y.; Long, P.; Wu, Y.

    2013-01-01

    Full text of the publication follows. The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verification of the models for Monte Carlo (MC) simulation are very tedious, error-prone and time-consuming. In addition, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling. The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients (Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection. (authors)

  8. Skull base tumours part I: Imaging technique, anatomy and anterior skull base tumours

    International Nuclear Information System (INIS)

    Borges, Alexandra

    2008-01-01

    Advances in cross-sectional imaging, surgical technique and adjuvant treatment have largely contributed to ameliorate the prognosis, lessen the morbidity and mortality of patients with skull base tumours and to the growing medical investment in the management of these patients. Because clinical assessment of the skull base is limited, cross-sectional imaging became indispensable in the diagnosis, treatment planning and follow-up of patients with suspected skull base pathology and the radiologist is increasingly responsible for the fate of these patients. This review will focus on the advances in imaging technique; contribution to patient's management and on the imaging features of the most common tumours affecting the anterior skull base. Emphasis is given to a systematic approach to skull base pathology based upon an anatomic division taking into account the major tissue constituents in each skull base compartment. The most relevant information that should be conveyed to surgeons and radiation oncologists involved in patient's management will be discussed

  9. Fully wireless pressure sensor based on endoscopy images

    Science.gov (United States)

    Maeda, Yusaku; Mori, Hirohito; Nakagawa, Tomoaki; Takao, Hidekuni

    2018-04-01

    In this paper, the result of developing a fully wireless pressure sensor based on endoscopy images for an endoscopic surgery is reported for the first time. The sensor device has structural color with a nm-scale narrow gap, and the gap is changed by air pressure. The structural color of the sensor is acquired from camera images. Pressure detection can be realized with existing endoscope configurations only. The inner air pressure of the human body should be measured under flexible-endoscope operation using the sensor. Air pressure monitoring, has two important purposes. The first is to quantitatively measure tumor size under a constant air pressure for treatment selection. The second purpose is to prevent the endangerment of a patient due to over transmission of air. The developed sensor was evaluated, and the detection principle based on only endoscopy images has been successfully demonstrated.

  10. Real-time particle image velocimetry based on FPGA technology

    International Nuclear Information System (INIS)

    Iriarte Munoz, Jose Miguel

    2008-01-01

    Particle image velocimetry (PIV), based on laser sheet, is a method for image processing and calculation of distributed velocity fields.It is well established as a fluid dynamics measurement tool, being applied to liquid, gases and multiphase flows.Images of particles are processed by means of computationally demanding algorithms, what makes its real-time implementation difficult.The most probable displacements are found applying two dimensional cross-correlation function. In this work, we detail how it is possible to achieve real-time visualization of PIV method by designing an adaptive embedded architecture based on FPGA technology.We show first results of a physical field of velocity calculated by this platform system in a real-time approach. [es

  11. Smartphone based scalable reverse engineering by digital image correlation

    Science.gov (United States)

    Vidvans, Amey; Basu, Saurabh

    2018-03-01

    There is a need for scalable open source 3D reconstruction systems for reverse engineering. This is because most commercially available reconstruction systems are capital and resource intensive. To address this, a novel reconstruction technique is proposed. The technique involves digital image correlation based characterization of surface speeds followed by normalization with respect to angular speed during rigid body rotational motion of the specimen. Proof of concept of the same is demonstrated and validated using simulation and empirical characterization. Towards this, smart-phone imaging and inexpensive off the shelf components along with those fabricated additively using poly-lactic acid polymer with a standard 3D printer are used. Some sources of error in this reconstruction methodology are discussed. It is seen that high curvatures on the surface suppress accuracy of reconstruction. Reasons behind this are delineated in the nature of the correlation function. Theoretically achievable resolution during smart-phone based 3D reconstruction by digital image correlation is derived.

  12. Wiener discrete cosine transform-based image filtering

    Science.gov (United States)

    Pogrebnyak, Oleksiy; Lukin, Vladimir V.

    2012-10-01

    A classical problem of additive white (spatially uncorrelated) Gaussian noise suppression in grayscale images is considered. The main attention is paid to discrete cosine transform (DCT)-based denoising, in particular, to image processing in blocks of a limited size. The efficiency of DCT-based image filtering with hard thresholding is studied for different sizes of overlapped blocks. A multiscale approach that aggregates the outputs of DCT filters having different overlapped block sizes is proposed. Later, a two-stage denoising procedure that presumes the use of the multiscale DCT-based filtering with hard thresholding at the first stage and a multiscale Wiener DCT-based filtering at the second stage is proposed and tested. The efficiency of the proposed multiscale DCT-based filtering is compared to the state-of-the-art block-matching and three-dimensional filter. Next, the potentially reachable multiscale filtering efficiency in terms of output mean square error (MSE) is studied. The obtained results are of the same order as those obtained by Chatterjee's approach based on nonlocal patch processing. It is shown that the ideal Wiener DCT-based filter potential is usually higher when noise variance is high.

  13. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  14. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  15. FACT. New image parameters based on the watershed-algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Linhoff, Lena; Bruegge, Kai Arno; Buss, Jens [TU Dortmund (Germany). Experimentelle Physik 5b; Collaboration: FACT-Collaboration

    2016-07-01

    FACT, the First G-APD Cherenkov Telescope, is the first imaging atmospheric Cherenkov telescope that is using Geiger-mode avalanche photodiodes (G-APDs) as photo sensors. The raw data produced by this telescope are processed in an analysis chain, which leads to a classification of the primary particle that induce a shower and to an estimation of its energy. One important step in this analysis chain is the parameter extraction from shower images. By the application of a watershed algorithm to the camera image, new parameters are computed. Perceiving the brightness of a pixel as height, a set of pixels can be seen as 'landscape' with hills and valleys. A watershed algorithm groups all pixels to a cluster that belongs to the same hill. From the emerging segmented image, one can find new parameters for later analysis steps, e.g. number of clusters, their shape and containing photon charge. For FACT data, the FellWalker algorithm was chosen from the class of watershed algorithms, because it was designed to work on discrete distributions, in this case the pixels of a camera image. The FellWalker algorithm is implemented in FACT-tools, which provides the low level analysis framework for FACT. This talk will focus on the computation of new, FellWalker based, image parameters, which can be used for the gamma-hadron separation. Additionally, their distributions concerning real and Monte Carlo Data are compared.

  16. Characterization of porcine eyes based on autofluorescence lifetime imaging

    Science.gov (United States)

    Batista, Ana; Breunig, Hans Georg; Uchugonova, Aisada; Morgado, António Miguel; König, Karsten

    2015-03-01

    Multiphoton microscopy is a non-invasive imaging technique with ideal characteristics for biological applications. In this study, we propose to characterize three major structures of the porcine eye, the cornea, crystalline lens, and retina using two-photon excitation fluorescence lifetime imaging microscopy (2PE-FLIM). Samples were imaged using a laser-scanning microscope, consisting of a broadband sub-15 femtosecond (fs) near-infrared laser. Signal detection was performed using a 16-channel photomultiplier tube (PMT) detector (PML-16PMT). Therefore, spectral analysis of the fluorescence lifetime data was possible. To ensure a correct spectral analysis of the autofluorescence lifetime data, the spectra of the individual endogenous fluorophores were acquired with the 16-channel PMT and with a spectrometer. All experiments were performed within 12h of the porcine eye enucleation. We were able to image the cornea, crystalline lens, and retina at multiple depths. Discrimination of each structure based on their autofluorescence intensity and lifetimes was possible. Furthermore, discrimination between different layers of the same structure was also possible. To the best of our knowledge, this was the first time that 2PE-FLIM was used for porcine lens imaging and layer discrimination. With this study we further demonstrated the feasibility of 2PE-FLIM to image and differentiate three of the main components of the eye and its potential as an ophthalmologic technique.

  17. Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

    Directory of Open Access Journals (Sweden)

    Yajing Shen

    2015-12-01

    Full Text Available Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

  18. Cloud-based processing of multi-spectral imaging data

    Science.gov (United States)

    Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

    2017-03-01

    Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

  19. POTENTIALS OF IMAGE BASED ACTIVE RANGING TO CAPTURE DYNAMIC SCENES

    Directory of Open Access Journals (Sweden)

    B. Jutzi

    2012-09-01

    Full Text Available Obtaining a 3D description of man-made and natural environments is a basic task in Computer Vision and Remote Sensing. To this end, laser scanning is currently one of the dominating techniques to gather reliable 3D information. The scanning principle inherently needs a certain time interval to acquire the 3D point cloud. On the other hand, new active sensors provide the possibility of capturing range information by images with a single measurement. With this new technique image-based active ranging is possible which allows capturing dynamic scenes, e.g. like walking pedestrians in a yard or moving vehicles. Unfortunately most of these range imaging sensors have strong technical limitations and are not yet sufficient for airborne data acquisition. It can be seen from the recent development of highly specialized (far-range imaging sensors – so called flash-light lasers – that most of the limitations could be alleviated soon, so that future systems will be equipped with improved image size and potentially expanded operating range. The presented work is a first step towards the development of methods capable for application of range images in outdoor environments. To this end, an experimental setup was set up for investigating these proposed possibilities. With the experimental setup a measurement campaign was carried out and first results will be presented within this paper.

  20. Remote Cherenkov imaging-based quality assurance of a magnetic resonance image-guided radiotherapy system.

    Science.gov (United States)

    Andreozzi, Jacqueline M; Mooney, Karen E; Brůža, Petr; Curcuru, Austen; Gladstone, David J; Pogue, Brian W; Green, Olga

    2018-06-01

    Tools to perform regular quality assurance of magnetic resonance image-guided radiotherapy (MRIgRT) systems should ideally be independent of interference from the magnetic fields. Remotely acquired optical Cherenkov imaging-based dosimetry measurements in water were investigated for this purpose, comparing measures of dose accuracy, temporal dynamics, and overall integrated IMRT delivery. A 40 × 30.5 × 37.5 cm 3 water tank doped with 1 g/L of quinine sulfate was imaged using an intensified charge-coupled device (ICCD) to capture the Cherenkov emission while being irradiated by a commercial MRIgRT system (ViewRay™). The ICCD was placed down-bore at the end of the couch, 4 m from treatment isocenter and behind the 5-Gauss line of the 0.35-T MRI. After establishing optimal camera acquisition settings, square beams of increasing size (4.2 × 4.2 cm 2 , 10.5 × 10.5 cm 2 , and 14.7 × 14.7 cm 2 ) were imaged at 0.93 frames per second, from an individual cobalt-60 treatment head, to develop projection measures related to percent depth dose (PDD) curves and cross beam profiles (CPB). These Cherenkov-derived measurements were compared to ionization chamber (IC) and radiographic film dosimetry data, as well as simulation data from the treatment planning system (TPS). An intensity-modulated radiotherapy (IMRT) commissioning plan from AAPM TG-119 (C4:C-Shape) was also imaged at 2.1 frames per second, and the single linear sum image from 509 s of plan delivery was compared to the dose volume prediction generated by the TPS using gamma index analysis. Analysis of standardized test target images (1024 × 1024 pixels) yielded a pixel resolution of 0.37 mm/pixel. The beam width measured from the Cherenkov image-generated projection CBPs was within 1 mm accuracy when compared to film measurements for all beams. The 502 point measurements (i.e., pixels) of the Cherenkov image-based projection percent depth dose curves (pPDDs) were compared to p

  1. Image-based navigation for a robotized flexible endoscope

    NARCIS (Netherlands)

    van der Stap, N.; Slump, Cornelis H.; Broeders, Ivo Adriaan Maria Johannes; van der Heijden, Ferdinand; Luo, Xiongbiao; Reichl, Tobias; Mirota, Daniel; Soper, Timothy

    2014-01-01

    Robotizing flexible endoscopy enables image-based control of endoscopes. Especially during high-throughput procedures, such as a colonoscopy, navigation support algorithms could improve procedure turnaround and ergonomics for the endoscopist. In this study, we have developed and implemented a

  2. Application of aerial image based information for coastal habitat research

    DEFF Research Database (Denmark)

    Juel, Anders

    2014-01-01

    and research in coastal terrestrial habitats. It further presents new insight into the mechanisms determining the spatial patterns of vegetation across coastal landscapes. These topics are investigated by combining fine-scale vegetation information from a comprehensive field programme with object-based image...

  3. Investigating Image-Based Perception and Reasoning in Geometry

    Science.gov (United States)

    Campbell, Stephen R.; Handscomb, Kerry; Zaparyniuk, Nicholas E.; Sha, Li; Cimen, O. Arda; Shipulina, Olga V.

    2009-01-01

    Geometry is required for many secondary school students, and is often learned, taught, and assessed more in a heuristic image-based manner, than as a formal axiomatic deductive system. Students are required to prove general theorems, but diagrams are usually used. It follows that understanding how students engage in perceiving and reasoning about…

  4. Cryptanalysis of a chaos-based image encryption algorithm

    International Nuclear Information System (INIS)

    Cokal, Cahit; Solak, Ercan

    2009-01-01

    A chaos-based image encryption algorithm was proposed in [Z.-H. Guan, F. Huang, W. Guan, Phys. Lett. A 346 (2005) 153]. In this Letter, we analyze the security weaknesses of the proposal. By applying chosen-plaintext and known-plaintext attacks, we show that all the secret parameters can be revealed

  5. Security Analysis of A Chaos-based Image Encryption Algorithm

    OpenAIRE

    Lian, Shiguo; Sun, Jinsheng; Wang, Zhiquan

    2006-01-01

    The security of Fridrich Image Encryption Algorithm against brute-force attack, statistical attack, known-plaintext attack and select-plaintext attack is analyzed by investigating the properties of the involved chaotic maps and diffusion functions. Based on the given analyses, some means are proposed to strengthen the overall performance of the focused cryptosystem.

  6. Can social tagged images aid concept-based video search?

    NARCIS (Netherlands)

    Setz, A.T.; Snoek, C.G.M.

    2009-01-01

    This paper seeks to unravel whether commonly available social tagged images can be exploited as a training resource for concept-based video search. Since social tags are known to be ambiguous, overly personalized, and often error prone, we place special emphasis on the role of disambiguation. We

  7. Image based brachytherapy planning with special reference to gynaecological cancers

    International Nuclear Information System (INIS)

    Kirisits, C.

    2008-01-01

    Cervical cancer is the most common cancer among women in India and one of the most frequent malignancies in Europe and in North America. In addition endometrium, vagina and vulva cancer are treated with brachytherapy. Especially for locally advanced cervix cancer the integration of image based brachytherapy planning into clinical routine is becoming a new standard for the future

  8. Lévy-based modelling in brain imaging

    DEFF Research Database (Denmark)

    Jónsdóttir, Kristjana Ýr; Rønn-Nielsen, Anders; Mouridsen, Kim

    2013-01-01

    example of magnetic resonance imaging scans that are non-Gaussian. For these data, simulations under the fitted models show that traditional methods based on Gaussian random field theory may leave small, but significant changes in signal level undetected, while these changes are detectable under a non...

  9. Psychoanalytic Bases for One's Image of God: Fact or Artifact?

    Science.gov (United States)

    Buri, John R.

    As a result of Freud's seminal postulations of the psychoanalytic bases for one's God-concept, it is a frequently accepted hypothesis that an individual's image of God is largely a reflection of experiences with and feelings toward one's own father. While such speculations as to an individual's phenomenological conceptions of God have an…

  10. Image feature extraction based on the camouflage effectiveness evaluation

    Science.gov (United States)

    Yuan, Xin; Lv, Xuliang; Li, Ling; Wang, Xinzhu; Zhang, Zhi

    2018-04-01

    The key step of camouflage effectiveness evaluation is how to combine the human visual physiological features, psychological features to select effectively evaluation indexes. Based on the predecessors' camo comprehensive evaluation method, this paper chooses the suitable indexes combining with the image quality awareness, and optimizes those indexes combining with human subjective perception. Thus, it perfects the theory of index extraction.

  11. Aspect-based Relevance Learning for Image Retrieval

    NARCIS (Netherlands)

    M.J. Huiskes (Mark)

    2005-01-01

    htmlabstractWe analyze the special structure of the relevance feedback learning problem, focusing particularly on the effects of image selection by partial relevance on the clustering behavior of feedback examples. We propose a scheme, aspect-based relevance learning, which guarantees that feedback

  12. Binary-space-partitioned images for resolving image-based visibility.

    Science.gov (United States)

    Fu, Chi-Wing; Wong, Tien-Tsin; Tong, Wai-Shun; Tang, Chi-Keung; Hanson, Andrew J

    2004-01-01

    We propose a novel 2D representation for 3D visibility sorting, the Binary-Space-Partitioned Image (BSPI), to accelerate real-time image-based rendering. BSPI is an efficient 2D realization of a 3D BSP tree, which is commonly used in computer graphics for time-critical visibility sorting. Since the overall structure of a BSP tree is encoded in a BSPI, traversing a BSPI is comparable to traversing the corresponding BSP tree. BSPI performs visibility sorting efficiently and accurately in the 2D image space by warping the reference image triangle-by-triangle instead of pixel-by-pixel. Multiple BSPIs can be combined to solve "disocclusion," when an occluded portion of the scene becomes visible at a novel viewpoint. Our method is highly automatic, including a tensor voting preprocessing step that generates candidate image partition lines for BSPIs, filters the noisy input data by rejecting outliers, and interpolates missing information. Our system has been applied to a variety of real data, including stereo, motion, and range images.

  13. Fast method of constructing image correlations to build a free network based on image multivocabulary trees

    Science.gov (United States)

    Zhan, Zongqian; Wang, Xin; Wei, Minglu

    2015-05-01

    In image-based three-dimensional (3-D) reconstruction, one topic of growing importance is how to quickly obtain a 3-D model from a large number of images. The retrieval of the correct and relevant images for the model poses a considerable technological challenge. The "image vocabulary tree" has been proposed as a method to search for similar images. However, a significant drawback of this approach is identified in its low time efficiency and barely satisfactory classification result. The method proposed is inspired by, and improves upon, some recent methods. Specifically, vocabulary quality is considered and multivocabulary trees are designed to improve the classification result. A marked improvement was, indeed, observed in our evaluation of the proposed method. To improve time efficiency, graphics processing unit (GPU) computer unified device architecture parallel computation is applied in the multivocabulary trees. The results of the experiments showed that the GPU was three to four times more efficient than the enumeration matching and CPU methods when the number of images is large. This paper presents a reliable reference method for the rapid construction of a free network to be used for the computing of 3-D information.

  14. A kernel-based multi-feature image representation for histopathology image classification

    International Nuclear Information System (INIS)

    Moreno J; Caicedo J Gonzalez F

    2010-01-01

    This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  15. A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J Carlos Moreno

    2010-09-01

    Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  16. [Identification of green tea brand based on hyperspectra imaging technology].

    Science.gov (United States)

    Zhang, Hai-Liang; Liu, Xiao-Li; Zhu, Feng-Le; He, Yong

    2014-05-01

    Hyperspectral imaging technology was developed to identify different brand famous green tea based on PCA information and image information fusion. First 512 spectral images of six brands of famous green tea in the 380 approximately 1 023 nm wavelength range were collected and principal component analysis (PCA) was performed with the goal of selecting two characteristic bands (545 and 611 nm) that could potentially be used for classification system. Then, 12 gray level co-occurrence matrix (GLCM) features (i. e., mean, covariance, homogeneity, energy, contrast, correlation, entropy, inverse gap, contrast, difference from the second-order and autocorrelation) based on the statistical moment were extracted from each characteristic band image. Finally, integration of the 12 texture features and three PCA spectral characteristics for each green tea sample were extracted as the input of LS-SVM. Experimental results showed that discriminating rate was 100% in the prediction set. The receiver operating characteristic curve (ROC) assessment methods were used to evaluate the LS-SVM classification algorithm. Overall results sufficiently demonstrate that hyperspectral imaging technology can be used to perform classification of green tea.

  17. Learning-based compressed sensing for infrared image super resolution

    Science.gov (United States)

    Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

    2016-05-01

    This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

  18. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  19. Interactive classification and content-based retrieval of tissue images

    Science.gov (United States)

    Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

    2002-11-01

    We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

  20. Digital image correlation based on a fast convolution strategy

    Science.gov (United States)

    Yuan, Yuan; Zhan, Qin; Xiong, Chunyang; Huang, Jianyong

    2017-10-01

    In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss-Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.