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

Monocular SLAM for autonomous robots with enhanced features initialization.

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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.

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.

A Highest Order Hypothesis Compatibility Test for Monocular SLAM

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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.

Preliminary Results for a Monocular Marker-Free Gait Measurement System

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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.

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

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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.

Monocular channels have a functional role in endogenous orienting.

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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.

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...

Ergonomic evaluation of ubiquitous computing with monocular head-mounted display

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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.

Recovery of neurofilament following early monocular deprivation

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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.

A low cost PSD-based monocular motion capture system

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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.

Stereo using monocular cues within the tensor voting framework.

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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.

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

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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.

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.

Short-Term Monocular Deprivation Enhances Physiological Pupillary Oscillations

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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.

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

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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.

Relating binocular and monocular vision in strabismic and anisometropic amblyopia.

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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.

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.

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.

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...

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.

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.

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

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).

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.

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 ...

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

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…

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.

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

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

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.

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.

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.

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.

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.

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.

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…

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...

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

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

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.

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.

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.

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

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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.

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.

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.

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.

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.

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

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,...

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.

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.

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)

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.

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.

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...

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

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

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.

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

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

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.

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

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.

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...

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.

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

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)

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.

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.

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.

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.

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.

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

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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

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

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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

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...

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

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

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.

[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.

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

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.

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.

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.

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination.

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-09-24

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective- n -Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal.

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

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...

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...

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."

Chronic imaging through "transparent skull" in mice.

Directory of Open Access Journals (Sweden)

Anna Steinzeig

Full Text Available Growing interest in long-term visualization of cortical structure and function requires methods that allow observation of an intact cortex in longitudinal imaging studies. Here we describe a detailed protocol for the "transparent skull" (TS preparation based on skull clearing with cyanoacrylate, which is applicable for long-term imaging through the intact skull in mice. We characterized the properties of the TS in imaging of intrinsic optical signals and compared them with the more conventional cranial window preparation. Our results show that TS is less invasive, maintains stabile transparency for at least two months, and compares favorably to data obtained from the conventional cranial window. We applied this method to experiments showing that a four-week treatment with the antidepressant fluoxetine combined with one week of monocular deprivation induced a shift in ocular dominance in the mouse visual cortex, confirming that fluoxetine treatment restores critical-period-like plasticity. Our results demonstrate that the TS preparation could become a useful method for long-term visualization of the living mouse brain.

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...

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

3-D model-based vehicle tracking.

Science.gov (United States)

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

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).

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.

Vision-based Vehicle Detection Survey

Directory of Open Access Journals (Sweden)

Alex David S

2016-03-01

Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

Long-Term Visual Training Increases Visual Acuity and Long-Term Monocular Deprivation Promotes Ocular Dominance Plasticity in Adult Standard Cage-Raised Mice.

Science.gov (United States)

Hosang, Leon; Yusifov, Rashad; Löwel, Siegrid

2018-01-01

For routine behavioral tasks, mice predominantly rely on olfactory cues and tactile information. In contrast, their visual capabilities appear rather restricted, raising the question whether they can improve if vision gets more behaviorally relevant. We therefore performed long-term training using the visual water task (VWT): adult standard cage (SC)-raised mice were trained to swim toward a rewarded grating stimulus so that using visual information avoided excessive swimming toward nonrewarded stimuli. Indeed, and in contrast to old mice raised in a generally enriched environment (Greifzu et al., 2016), long-term VWT training increased visual acuity (VA) on average by more than 30% to 0.82 cycles per degree (cyc/deg). In an individual animal, VA even increased to 1.49 cyc/deg, i.e., beyond the rat range of VAs. Since visual experience enhances the spatial frequency threshold of the optomotor (OPT) reflex of the open eye after monocular deprivation (MD), we also quantified monocular vision after VWT training. Monocular VA did not increase reliably, and eye reopening did not initiate a decline to pre-MD values as observed by optomotry; VA values rather increased by continued VWT training. Thus, optomotry and VWT measure different parameters of mouse spatial vision. Finally, we tested whether long-term MD induced ocular dominance (OD) plasticity in the visual cortex of adult [postnatal day (P)162-P182] SC-raised mice. This was indeed the case: 40-50 days of MD induced OD shifts toward the open eye in both VWT-trained and, surprisingly, also in age-matched mice without VWT training. These data indicate that (1) long-term VWT training increases adult mouse VA, and (2) long-term MD induces OD shifts also in adult SC-raised mice.

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

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�

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.

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

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

Science.gov (United States)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

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.

Binocular contrast-gain control for natural scenes: Image structure and phase alignment.

Science.gov (United States)

Huang, Pi-Chun; Dai, Yu-Ming

2018-05-01

In the context of natural scenes, we applied the pattern-masking paradigm to investigate how image structure and phase alignment affect contrast-gain control in binocular vision. We measured the discrimination thresholds of bandpass-filtered natural-scene images (targets) under various types of pedestals. Our first experiment had four pedestal types: bandpass-filtered pedestals, unfiltered pedestals, notch-filtered pedestals (which enabled removal of the spatial frequency), and misaligned pedestals (which involved rotation of unfiltered pedestals). Our second experiment featured six types of pedestals: bandpass-filtered, unfiltered, and notch-filtered pedestals, and the corresponding phase-scrambled pedestals. The thresholds were compared for monocular, binocular, and dichoptic viewing configurations. The bandpass-filtered pedestal and unfiltered pedestals showed classic dipper shapes; the dipper shapes of the notch-filtered, misaligned, and phase-scrambled pedestals were weak. We adopted a two-stage binocular contrast-gain control model to describe our results. We deduced that the phase-alignment information influenced the contrast-gain control mechanism before the binocular summation stage and that the phase-alignment information and structural misalignment information caused relatively strong divisive inhibition in the monocular and interocular suppression stages. When the pedestals were phase-scrambled, the elimination of the interocular suppression processing was the most convincing explanation of the results. Thus, our results indicated that both phase-alignment information and similar image structures cause strong interocular suppression. Copyright © 2018 Elsevier Ltd. All rights reserved.

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...

Development of a Vision-Based Robotic Follower Vehicle

Science.gov (United States)

2009-02-01

resultant blob . . . . . . . . . . 14 Figure 13: A sample image and the recognized keypoints found using the SIFT algorithm...Figure 12: An example of a spherical target and the resultant blob (taken from [66]). To track multi-coloured objects, rather than using just one...International Journal of Advanced Robotic Systems, 2(3), 245–250. [37] Zhou, J. and Clark, C. (2006), Autonomous fish tracking by ROV using Monocular

Percepção monocular da profundidade ou relevo na ilusão da máscara côncava na esquizofrenia

Directory of Open Access Journals (Sweden)

Arthur Alves

2014-03-01

Full Text Available Este trabalho foi desenvolvido com o propósito de investigar a percepção monocular da profundidade ou relevo da máscara côncava por 29 indivíduos saudáveis, sete indivíduos com esquizofrenia sob uso de antipsicótico por um período inferior ou igual a quatro semanas e 29 sob uso de antipsicótico por um período superior a quatro semanas. Os três grupos classificaram o reverso de uma máscara policromada em duas situações de iluminação, por cima e por baixo. Os resultados indicaram que a maioria dos indivíduos com esquizofrenia inverteu a profundidade da máscara côncava na condição de observação monocular e perceberam-na como convexa, sendo, portanto, suscetíveis à ilusão da máscara côncava. Os indivíduos com esquizofrenia sob uso de medicação antipsicótica pelo período superior a quatro semanas estimaram a convexidade da máscara côncava iluminada por cima em menor comprimento comparados aos indivíduos saudáveis.

The effect of image position on the Independent Components of natural binocular images.

Science.gov (United States)

Hunter, David W; Hibbard, Paul B

2018-01-11

Human visual performance degrades substantially as the angular distance from the fovea increases. This decrease in performance is found for both binocular and monocular vision. Although analysis of the statistics of natural images has provided significant insights into human visual processing, little research has focused on the statistical content of binocular images at eccentric angles. We applied Independent Component Analysis to rectangular image patches cut from locations within binocular images corresponding to different degrees of eccentricity. The distribution of components learned from the varying locations was examined to determine how these distributions varied across eccentricity. We found a general trend towards a broader spread of horizontal and vertical position disparity tunings in eccentric regions compared to the fovea, with the horizontal spread more pronounced than the vertical spread. Eccentric locations above the centroid show a strong bias towards far-tuned components, eccentric locations below the centroid show a strong bias towards near-tuned components. These distributions exhibit substantial similarities with physiological measurements in V1, however in common with previous research we also observe important differences, in particular distributions of binocular phase disparity which do not match physiology.

Theoretical Design and First Test in Laboratory of a Composite Visual Servo-Based Target Spray Robotic System

Directory of Open Access Journals (Sweden)

Dongjie Zhao

2016-01-01

Full Text Available In order to spray onto the canopy of interval planting crop, an approach of using a target spray robot with a composite vision servo system based on monocular scene vision and monocular eye-in-hand vision was proposed. Scene camera was used to roughly locate target crop, and then the image-processing methods for background segmentation, crop canopy centroid extraction, and 3D positioning were studied. Eye-in-hand camera was used to precisely determine spray position of each crop. Based on the center and area of 2D minimum-enclosing-circle (MEC of crop canopy, a method to calculate spray position and spray time was determined. In addition, locating algorithm for the MEC center in nozzle reference frame and the hand-eye calibration matrix were studied. The processing of a mechanical arm guiding nozzle to spray was divided into three stages: reset, alignment, and hovering spray, and servo method of each stage was investigated. For preliminary verification of the theoretical studies on the approach, a simplified experimental prototype containing one spray mechanical arm was built and some performance tests were carried out under controlled environment in laboratory. The results showed that the prototype could achieve the effect of “spraying while moving and accurately spraying on target.”

Fusion and rivalry are dependent on the perceptual meaning of visual stimuli.

Science.gov (United States)

Andrews, Timothy J; Lotto, R Beau

2004-03-09

We view the world with two eyes and yet are typically only aware of a single, coherent image. Arguably the simplest explanation for this is that the visual system unites the two monocular stimuli into a common stream that eventually leads to a single coherent sensation. However, this notion is inconsistent with the well-known phenomenon of rivalry; when physically different stimuli project to the same retinal location, the ensuing perception alternates between the two monocular views in space and time. Although fundamental for understanding the principles of binocular vision and visual awareness, the mechanisms under-lying binocular rivalry remain controversial. Specifically, there is uncertainty about what determines whether monocular images undergo fusion or rivalry. By taking advantage of the perceptual phenomenon of color contrast, we show that physically identical monocular stimuli tend to rival-not fuse-when they signify different objects at the same location in visual space. Conversely, when physically different monocular stimuli are likely to represent the same object at the same location in space, fusion is more likely to result. The data suggest that what competes for visual awareness in the two eyes is not the physical similarity between images but the similarity in their perceptual/empirical meaning.

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.

Effects of brief daily periods of unrestricted vision during early monocular form deprivation on development of visual area 2.

Science.gov (United States)

Zhang, Bin; Tao, Xiaofeng; Wensveen, Janice M; Harwerth, Ronald S; Smith, Earl L; Chino, Yuzo M

2011-09-14

Providing brief daily periods of unrestricted vision during early monocular form deprivation reduces the depth of amblyopia. To gain insights into the neural basis of the beneficial effects of this treatment, the binocular and monocular response properties of neurons were quantitatively analyzed in visual area 2 (V2) of form-deprived macaque monkeys. Beginning at 3 weeks of age, infant monkeys were deprived of clear vision in one eye for 12 hours every day until 21 weeks of age. They received daily periods of unrestricted vision for 0, 1, 2, or 4 hours during the form-deprivation period. After behavioral testing to measure the depth of the resulting amblyopia, microelectrode-recording experiments were conducted in V2. The ocular dominance imbalance away from the affected eye was reduced in the experimental monkeys and was generally proportional to the reduction in the depth of amblyopia in individual monkeys. There were no interocular differences in the spatial properties of V2 neurons in any subject group. However, the binocular disparity sensitivity of V2 neurons was significantly higher and binocular suppression was lower in monkeys that had unrestricted vision. The decrease in ocular dominance imbalance in V2 was the neuronal change most closely associated with the observed reduction in the depth of amblyopia. The results suggest that the degree to which extrastriate neurons can maintain functional connections with the deprived eye (i.e., reducing undersampling for the affected eye) is the most significant factor associated with the beneficial effects of brief periods of unrestricted vision.

Vision based persistent localization of a humanoid robot for locomotion tasks

Directory of Open Access Journals (Sweden)

Martínez Pablo A.

2016-09-01

Full Text Available Typical monocular localization schemes involve a search for matches between reprojected 3D world points and 2D image features in order to estimate the absolute scale transformation between the camera and the world. Successfully calculating such transformation implies the existence of a good number of 3D points uniformly distributed as reprojected pixels around the image plane. This paper presents a method to control the march of a humanoid robot towards directions that are favorable for visual based localization. To this end, orthogonal diagonalization is performed on the covariance matrices of both sets of 3D world points and their 2D image reprojections. Experiments with the NAO humanoid platform show that our method provides persistence of localization, as the robot tends to walk towards directions that are desirable for successful localization. Additional tests demonstrate how the proposed approach can be incorporated into a control scheme that considers reaching a target position.

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

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...

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.

Design of and normative data for a new computer based test of ocular torsion.

Science.gov (United States)

Vaswani, Reena S; Mudgil, Ananth V

2004-01-01

To evaluate a new clinically practical and dynamic test for quantifying torsional binocular eye alignment changes which may occur in the change from monocular to binocular viewing conditions. The test was developed using a computer with Lotus Freelance Software, binoculars with prisms and colored filters. The subject looks through binoculars at the computer screen two meters away. For monocular vision, six concentric blue circles, a blue horizontal line and a tilted red line were displayed on the screen. For binocular vision, white circles replaced blue circles. The subject was asked to orient the lines parallel to each other. The difference in tilt (degrees) between the subjective parallel and fixed horizontal position is the torsional alignment of the eye. The time to administer the test was approximately two minutes. In 70 Normal subjects, average age 16 years, the mean degree of cyclodeviation tilt in the right eye was 0.6 degrees for monocular viewing conditions and 0.7 degrees for binocular viewing conditions, with a standard deviation of approximately one degree. There was no "statistically significant" difference between monocular and binocular viewing. This computer based test is a simple, computerized, non-invasive test that has a potential for use in the diagnosis of cyclovertical strabismus. Currently, there is no commercially available test for this purpose.

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.

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.

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.

Contribution to the tracking and the 3D reconstruction of scenes composed of torus from image sequences a acquired by a moving camera; Contribution au suivi et a la reconstruction de scenes constituees d`objet toriques a partir de sequences d`images acquises par une camera mobile

Energy Technology Data Exchange (ETDEWEB)

Naudet, S

1997-01-31

The three-dimensional perception of the environment is often necessary for a robot to correctly perform its tasks. One solution, based on the dynamic vision, consists in analysing time-varying monocular images to estimate the spatial geometry of the scene. This thesis deals with the reconstruction of torus by dynamic vision. Though this object class is restrictive, it enables to tackle the problem of reconstruction of bent pipes usually encountered in industrial environments. The proposed method is based on the evolution of apparent contours of objects in the sequence. Using the expression of torus limb boundaries, it is possible to recursively estimate the object three-dimensional parameters by minimising the error between the predicted projected contours and the image contours. This process, which is performed by a Kalman filter, does not need a precise knowledge of the camera displacement or any matching of the tow limbs belonging to the same object. To complete this work, temporal tracking of objects which deals with occlusion situations is proposed. The approach consists in modeling and interpreting the apparent motion of objects in the successive images. The motion interpretation, based on a simplified representation of the scene, allows to recover pertinent three-dimensional information which is used to manage occlusion situations. Experiments, on synthetic and real images, proves he validity of the tracking and the reconstruction processes. (author) 127 refs.

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.

VISIDEP™: visual image depth enhancement by parallax induction

Science.gov (United States)

Jones, Edwin R.; McLaurin, A. P.; Cathey, LeConte

1984-05-01

The usual descriptions of depth perception have traditionally required the simultaneous presentation of disparate views presented to separate eyes with the concomitant demand that the resulting binocular parallax be horizontally aligned. Our work suggests that the visual input information is compared in a short-term memory buffer which permits the brain to compute depth as it is normally perceived. However, the mechanism utilized is also capable of receiving and processing the stereographic information even when it is received monocularly or when identical inputs are simultaneously fed to both eyes. We have also found that the restriction to horizontally displaced images is not a necessary requirement and that improvement in image acceptability is achieved by the use of vertical parallax. Use of these ideas permit the presentation of three-dimensional scenes on flat screens in full color without the encumbrance of glasses or other viewing aids.

Towards real-time body pose estimation for presenters in meeting environments

NARCIS (Netherlands)

Poppe, Ronald Walter; Heylen, Dirk K.J.; Nijholt, Antinus; Poel, Mannes

2005-01-01

This paper describes a computer vision-based approach to body pose estimation. The algorithm can be executed in real-time and processes low resolution, monocular image sequences. A silhouette is extracted and matched against a projection of a 16 DOF human body model. In addition, skin color is used

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...

Measuring Algorithm for the Distance to a Preceding Vehicle on Curve Road Using On-Board Monocular Camera

Science.gov (United States)

Yu, Guizhen; Zhou, Bin; Wang, Yunpeng; Wun, Xinkai; Wang, Pengcheng

2015-12-01

Due to more severe challenges of traffic safety problems, the Advanced Driver Assistance Systems (ADAS) has received widespread attention. Measuring the distance to a preceding vehicle is important for ADAS. However, the existing algorithm focuses more on straight road sections than on curve measurements. In this paper, we present a novel measuring algorithm for the distance to a preceding vehicle on a curve road using on-board monocular camera. Firstly, the characteristics of driving on the curve road is analyzed and the recognition of the preceding vehicle road area is proposed. Then, the vehicle detection and distance measuring algorithms are investigated. We have verified these algorithms on real road driving. The experimental results show that this method proposed in the paper can detect the preceding vehicle on curve roads and accurately calculate the longitudinal distance and horizontal distance to the preceding vehicle.

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.

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.

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.

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

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Contribution to the tracking and the 3D reconstruction of scenes composed of torus from image sequences a acquired by a moving camera

International Nuclear Information System (INIS)

Naudet, S.

1997-01-01

The three-dimensional perception of the environment is often necessary for a robot to correctly perform its tasks. One solution, based on the dynamic vision, consists in analysing time-varying monocular images to estimate the spatial geometry of the scene. This thesis deals with the reconstruction of torus by dynamic vision. Though this object class is restrictive, it enables to tackle the problem of reconstruction of bent pipes usually encountered in industrial environments. The proposed method is based on the evolution of apparent contours of objects in the sequence. Using the expression of torus limb boundaries, it is possible to recursively estimate the object three-dimensional parameters by minimising the error between the predicted projected contours and the image contours. This process, which is performed by a Kalman filter, does not need a precise knowledge of the camera displacement or any matching of the tow limbs belonging to the same object. To complete this work, temporal tracking of objects which deals with occlusion situations is proposed. The approach consists in modeling and interpreting the apparent motion of objects in the successive images. The motion interpretation, based on a simplified representation of the scene, allows to recover pertinent three-dimensional information which is used to manage occlusion situations. Experiments, on synthetic and real images, proves he validity of the tracking and the reconstruction processes. (author)

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...

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.

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.

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....

Meta-image navigation augmenters for unmanned aircraft systems (MINA for UAS)

Science.gov (United States)

Òªelik, Koray; Somani, Arun K.; Schnaufer, Bernard; Hwang, Patrick Y.; McGraw, Gary A.; Nadke, Jeremy

2013-05-01

GPS is a critical sensor for Unmanned Aircraft Systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta Image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.

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

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.

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

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....

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.

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.

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.

NSCT BASED LOCAL ENHANCEMENT FOR ACTIVE CONTOUR BASED IMAGE SEGMENTATION APPLICATION

Directory of Open Access Journals (Sweden)

Hiren Mewada

2010-08-01

Full Text Available Because of cross-disciplinary nature, Active Contour modeling techniques have been utilized extensively for the image segmentation. In traditional active contour based segmentation techniques based on level set methods, the energy functions are defined based on the intensity gradient. This makes them highly sensitive to the situation where the underlying image content is characterized by image nonhomogeneities due to illumination and contrast condition. This is the most difficult problem to make them as fully automatic image segmentation techniques. This paper introduces one of the approaches based on image enhancement to this problem. The enhanced image is obtained using NonSubsampled Contourlet Transform, which improves the edges strengths in the direction where the illumination is not proper and then active contour model based on level set technique is utilized to segment the object. Experiment results demonstrate that proposed method can be utilized along with existing active contour model based segmentation method under situation characterized by intensity non-homogeneity to make them fully automatic.

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.

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.

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.

Tundish Cover Flux Thickness Measurement Method and Instrumentation Based on Computer Vision in Continuous Casting Tundish

Directory of Open Access Journals (Sweden)

Meng Lu

2013-01-01

Full Text Available Thickness of tundish cover flux (TCF plays an important role in continuous casting (CC steelmaking process. Traditional measurement method of TCF thickness is single/double wire methods, which have several problems such as personal security, easily affected by operators, and poor repeatability. To solve all these problems, in this paper, we specifically designed and built an instrumentation and presented a novel method to measure the TCF thickness. The instrumentation was composed of a measurement bar, a mechanical device, a high-definition industrial camera, a Siemens S7-200 programmable logic controller (PLC, and a computer. Our measurement method was based on the computer vision algorithms, including image denoising method, monocular range measurement method, scale invariant feature transform (SIFT, and image gray gradient detection method. Using the present instrumentation and method, images in the CC tundish can be collected by camera and transferred to computer to do imaging processing. Experiments showed that our instrumentation and method worked well at scene of steel plants, can accurately measure the thickness of TCF, and overcome the disadvantages of traditional measurement methods, or even replace the traditional ones.

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.

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.

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.

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.

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.

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.

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.

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

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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.

A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

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T. Kavzoglu

2016-06-01

Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

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

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.

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.)

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.

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.

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.

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

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.

The iPod binocular home-based treatment for amblyopia in adults: efficacy and compliance.

Science.gov (United States)

Hess, Robert F; Babu, Raiju Jacob; Clavagnier, Simon; Black, Joanna; Bobier, William; Thompson, Benjamin

2014-09-01

Occlusion therapy for amblyopia is predicated on the idea that amblyopia is primarily a disorder of monocular vision; however, there is growing evidence that patients with amblyopia have a structurally intact binocular visual system that is rendered functionally monocular due to suppression. Furthermore, we have found that a dichoptic treatment intervention designed to directly target suppression can result in clinically significant improvement in both binocular and monocular visual function in adult patients with amblyopia. The fact that monocular improvement occurs in the absence of any fellow eye occlusion suggests that amblyopia is, in part, due to chronic suppression. Previously the treatment has been administered as a psychophysical task and more recently as a video game that can be played on video goggles or an iPod device equipped with a lenticular screen. The aim of this case-series study of 14 amblyopes (six strabismics, six anisometropes and two mixed) ages 13 to 50 years was to investigate: 1. whether the portable video game treatment is suitable for at-home use and 2. whether an anaglyphic version of the iPod-based video game, which is more convenient for at-home use, has comparable effects to the lenticular version. The dichoptic video game treatment was conducted at home and visual functions assessed before and after treatment. We found that at-home use for 10 to 30 hours restored simultaneous binocular perception in 13 of 14 cases along with significant improvements in acuity (0.11 ± 0.08 logMAR) and stereopsis (0.6 ± 0.5 log units). Furthermore, the anaglyph and lenticular platforms were equally effective. In addition, the iPod devices were able to record a complete and accurate picture of treatment compliance. The home-based dichoptic iPod approach represents a viable treatment for adults with amblyopia. © 2014 The Authors. Clinical and Experimental Optometry © 2014 Optometrists Association Australia.

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

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....

[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.

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.

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.

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.

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.

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

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.

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.

Retinal image quality during accommodation.

Science.gov (United States)

López-Gil, Norberto; Martin, Jesson; Liu, Tao; Bradley, Arthur; Díaz-Muñoz, David; Thibos, Larry N

2013-07-01

We asked if retinal image quality is maximum during accommodation, or sub-optimal due to accommodative error, when subjects perform an acuity task. Subjects viewed a monochromatic (552 nm), high-contrast letter target placed at various viewing distances. Wavefront aberrations of the accommodating eye were measured near the endpoint of an acuity staircase paradigm. Refractive state, defined as the optimum target vergence for maximising retinal image quality, was computed by through-focus wavefront analysis to find the power of the virtual correcting lens that maximizes visual Strehl ratio. Despite changes in ocular aberrations and pupil size during binocular viewing, retinal image quality and visual acuity typically remain high for all target vergences. When accommodative errors lead to sub-optimal retinal image quality, acuity and measured image quality both decline. However, the effect of accommodation errors of on visual acuity are mitigated by pupillary constriction associated with accommodation and binocular convergence and also to binocular summation of dissimilar retinal image blur. Under monocular viewing conditions some subjects displayed significant accommodative lag that reduced visual performance, an effect that was exacerbated by pharmacological dilation of the pupil. Spurious measurement of accommodative error can be avoided when the image quality metric used to determine refractive state is compatible with the focusing criteria used by the visual system to control accommodation. Real focusing errors of the accommodating eye do not necessarily produce a reliably measurable loss of image quality or clinically significant loss of visual performance, probably because of increased depth-of-focus due to pupil constriction. When retinal image quality is close to maximum achievable (given the eye's higher-order aberrations), acuity is also near maximum. A combination of accommodative lag, reduced image quality, and reduced visual function may be a useful

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)

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.

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.

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

Hierarchical online appearance-based tracking for 3D head pose, eyebrows, lips, eyelids, and irises

NARCIS (Netherlands)

Orozco, Javier; Rudovic, Ognjen; Gonzalez Garcia, Jordi; Pantic, Maja

In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can

Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

Directory of Open Access Journals (Sweden)

Chunfu Wu

2015-01-01

Full Text Available For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when object’s imaging depth and camera’s position extrinsic parameters are unknown. Firstly, the homography’s particular properties caused by mobile robot’s 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view’s single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and camera’s position extrinsic parameters.

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.

Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

Science.gov (United States)

Dostal, P.; Krasula, L.; Klima, M.

2012-06-01

Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

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.

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.

Layer 2/3 synapses in monocular and binocular regions of tree shrew visual cortex express mAChR-dependent long-term depression and long-term potentiation.

Science.gov (United States)

McCoy, Portia; Norton, Thomas T; McMahon, Lori L

2008-07-01

Acetylcholine is an important modulator of synaptic efficacy and is required for learning and memory tasks involving the visual cortex. In rodent visual cortex, activation of muscarinic acetylcholine receptors (mAChRs) induces a persistent long-term depression (LTD) of transmission at synapses recorded in layer 2/3 of acute slices. Although the rodent studies expand our knowledge of how the cholinergic system modulates synaptic function underlying learning and memory, they are not easily extrapolated to more complex visual systems. Here we used tree shrews for their similarities to primates, including a visual cortex with separate, defined regions of monocular and binocular innervation, to determine whether mAChR activation induces long-term plasticity. We find that the cholinergic agonist carbachol (CCh) not only induces long-term plasticity, but the direction of the plasticity depends on the subregion. In the monocular region, CCh application induces LTD of the postsynaptic potential recorded in layer 2/3 that requires activation of m3 mAChRs and a signaling cascade that includes activation of extracellular signal-regulated kinase (ERK) 1/2. In contrast, layer 2/3 postsynaptic potentials recorded in the binocular region express long-term potentiation (LTP) following CCh application that requires activation of m1 mAChRs and phospholipase C. Our results show that activation of mAChRs induces long-term plasticity at excitatory synapses in tree shrew visual cortex. However, depending on the ocular inputs to that region, variation exists as to the direction of plasticity, as well as to the specific mAChR and signaling mechanisms that are required.

A Novel Optimization-Based Approach for Content-Based Image Retrieval

Directory of Open Access Journals (Sweden)

Manyu Xiao

2013-01-01

Full Text Available Content-based image retrieval is nowadays one of the possible and promising solutions to manage image databases effectively. However, with the large number of images, there still exists a great discrepancy between the users’ expectations (accuracy and efficiency and the real performance in image retrieval. In this work, new optimization strategies are proposed on vocabulary tree building, retrieval, and matching methods. More precisely, a new clustering strategy combining classification and conventional K-Means method is firstly redefined. Then a new matching technique is built to eliminate the error caused by large-scaled scale-invariant feature transform (SIFT. Additionally, a new unit mechanism is proposed to reduce the cost of indexing time. Finally, the numerical results show that excellent performances are obtained in both accuracy and efficiency based on the proposed improvements for image retrieval.

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.

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.

Could visual neglect induce amblyopia?

Science.gov (United States)

Bier, J C; Vokaer, M; Fery, P; Garbusinski, J; Van Campenhoudt, G; Blecic, S A; Bartholomé, E J

2004-12-01

Oculomotor nerve disease is a common cause of diplopia. When strabismus is present, absence of diplopia has to induce the research of either uncovering of visual fields or monocular suppression, amblyopia or blindness. We describe the case of a 41-year-old woman presenting with right oculomotor paresis and left object-centred visual neglect due to a right fronto-parietal haemorrhage expanding to the right peri-mesencephalic cisterna caused by the rupture of a right middle cerebral artery aneurysm. She never complained of diplopia despite binocular vision and progressive recovery of strabismus, excluding uncovering of visual fields. Since all other causes were excluded in this case, we hypothesise that the absence of diplopia was due to the object-centred visual neglect. Partial internal right oculomotor paresis causes an ocular deviation in abduction; the image being perceived deviated contralaterally to the left. Thus, in our case, the neglect of the left image is equivalent to a right monocular functional blindness. However, bell cancellation test clearly worsened when assessed in left monocular vision confirming that eye patching can worsen attentional visual neglect. In conclusion, our case argues for the possibility of a functional monocular blindness induced by visual neglect. We think that in presence of strabismus, absence of diplopia should induce the search for hemispatial visual neglect when supratentorial lesions are suspected.

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.

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

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.

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.

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 ...

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.

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.

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.

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.

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.

New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

Science.gov (United States)

Boushey, C J; Spoden, M; Zhu, F M; Delp, E J; Kerr, D A

2017-08-01

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

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.

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.

Research of Obstacle Recognition Technology in Cross-Country Environment for Unmanned Ground Vehicle

Directory of Open Access Journals (Sweden)

Zhao Yibing

2014-01-01

Full Text Available Being aimed at the obstacle recognition problem of unmanned ground vehicles in cross-country environment, this paper uses monocular vision sensor to realize the obstacle recognition of typical obstacles. Firstly, median filtering algorithm is applied during image preprocessing that can eliminate the noise. Secondly, image segmentation method based on the Fisher criterion function is used to segment the region of interest. Then, morphological method is used to process the segmented image, which is preparing for the subsequent analysis. The next step is to extract the color feature S, color feature a and edge feature “verticality” of image are extracted based on the HSI color space, the Lab color space, and two value images. Finally multifeature fusion algorithm based on Bayes classification theory is used for obstacle recognition. Test results show that the algorithm has good robustness and accuracy.

Comparison on Integer Wavelet Transforms in Spherical Wavelet Based Image Based Relighting

Institute of Scientific and Technical Information of China (English)

WANGZe; LEEYin; LEUNGChising; WONGTientsin; ZHUYisheng

2003-01-01

To provide a good quality rendering in the Image based relighting (IBL) system, tremendous reference images under various illumination conditions are needed. Therefore data compression is essential to enable interactive action. And the rendering speed is another crucial consideration for real applications. Based on Spherical wavelet transform (SWT), this paper presents a quick representation method with Integer wavelet transform (IWT) for the IBL system. It focuses on comparison on different IWTs with the Embedded zerotree wavelet (EZW) used in the IBL system. The whole compression procedure contains two major compression steps. Firstly, SWT is applied to consider the correlation among different reference images. Secondly, the SW transformed images are compressed with IWT based image compression approach. Two IWTs are used and good results are showed in the simulations.

High-speed MRF-based segmentation algorithm using pixonal images

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Hassanpour, H.; Naimi, H. M.

2013-01-01

Segmentation is one of the most complicated procedures in the image processing that has important role in the image analysis. In this paper, an improved pixon-based method for image segmentation is proposed. In proposed algorithm, complex partial differential equations (PDEs) is used as a kernel...... function to make pixonal image. Using this kernel function causes noise on images to reduce and an image not to be over-segment when the pixon-based method is used. Utilising the PDE-based method leads to elimination of some unnecessary details and results in a fewer pixon number, faster performance...... and more robustness against unwanted environmental noises. As the next step, the appropriate pixons are extracted and eventually, we segment the image with the use of a Markov random field. The experimental results indicate that the proposed pixon-based approach has a reduced computational load...

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

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.

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.

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.

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.

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 ...

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.

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.

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.

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.

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.

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)

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.

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.

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.

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.

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.

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...

Skull base tumours part I: Imaging technique, anatomy and anterior skull base tumours

Energy Technology Data Exchange (ETDEWEB)

Borges, Alexandra [Instituto Portugues de Oncologia Francisco Gentil, Centro de Lisboa, Servico de Radiologia, Rua Professor Lima Basto, 1093 Lisboa Codex (Portugal)], E-mail: borgesalexandra@clix.pt

2008-06-15

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.

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

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

Science.gov (United States)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

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%.

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...

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.

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.

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.

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)

GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

Science.gov (United States)

Xie, Lang; Luo, Yi-han; Bao, Qi-liang

2013-08-01

GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

The Computer Image Generation Applications Study.

Science.gov (United States)

1980-07-01

1059 7 T62 Tank 759 0 Lexington Carrier 1485 19 Sea Scape 600 1680 Fresnel Lens Optical Landing System (FLOLS) 20 0 Meatball 9 0 T37 Aircraft (LOD#3... Meatball T37 Aircraft NATO 4655 1914 33 new eye point. See also 7.1.5.5 for definition of monocular movement parallax. (g) Multiple Simulations

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.

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.

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.

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.

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.

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

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

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…

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.

Tag-Based Social Image Search: Toward Relevant and Diverse Results

Science.gov (United States)

Yang, Kuiyuan; Wang, Meng; Hua, Xian-Sheng; Zhang, Hong-Jiang

Recent years have witnessed a great success of social media websites. Tag-based image search is an important approach to access the image content of interest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the content of images and their associated tags. First, it estimates the relevance scores of images with respect to the query term based on both visual information of images and semantic information of associated tags. Then semantic similarities of social images are estimated based on their tags. Based on the relevance scores and the similarities, the ranking list is generated by a greedy ordering algorithm which optimizes Average Diverse Precision (ADP), a novel measure that is extended from the conventional Average Precision (AP). Comprehensive experiments and user studies demonstrate the effectiveness of the approach.

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.

[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.

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....

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.

Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion

Science.gov (United States)

Preibisch, Stephan; Rohlfing, Torsten; Hasak, Michael P.; Tomancak, Pavel

2008-03-01

Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.

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.

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)

Image noise-based dose adaptation in dynamic volume CT of the heart: dose and image quality optimisation in comparison with BMI-based dose adaptation

Energy Technology Data Exchange (ETDEWEB)

Odedra, Devang [Queen' s University, School of Medicine, Kingston, ON (Canada); Blobel, Joerg [Toshiba Medical Systems Europe BV, Zoetermeer (Netherlands); University of Toronto, Division of Cardiothoracic Imaging, Department of Medical Imaging, Toronto General Hospital, Toronto, ON (Canada); AlHumayyd, Saad; Durand, Miranda; Jimenez-Juan, Laura; Paul, Narinder [University of Toronto, Division of Cardiothoracic Imaging, Department of Medical Imaging, Toronto General Hospital, Toronto, ON (Canada)

2014-01-15

To compare the image quality and radiation dose using image-noise (IN)-based determination of X-ray tube settings compared with a body mass index (BMI)-based protocol during CT coronary angiography (CTCA). Two hundred consecutive patients referred for CTCA to our institution were divided into two groups: BMI-based, 100 patients had CTCA with the X-ray tube current adjusted to the patient's BMI while maintaining a fixed tube potential of 120 kV; IN-based, 100 patients underwent imaging with the X-ray tube current and voltage adjusted to the IN measured within the mid-left ventricle on a pre-acquisition trans-axial image. Two independent cardiac radiologists performed blinded image quality assessment with quantification of the IN and signal-to-noise ratio (SNR) from the mid-LV and qualitative assessment using a three-point score. Radiation dose (CTDI and DLP) was recorded from the console. Results showed: IN (HU): BMI-based, 30.1 ± 9.9; IN-based, 33.1 ± 6.7; 32 % variation reduction (P = 0.001); SNR: BMI-based, 18.6 ± 7.1; IN-based, 15.4 ± 3.7; 48 % variation reduction (P < 0.0001). Visual scores: BMI-based, 2.3 ± 0.6; IN-based, 2.2 ± 0.5 (P = 0.54). Radiation dose: CTDI (mGy), BMI-based, 22.68 ± 8.9; IN-based, 17.16 ± 7.6; 24.3 % reduction (P < 0.001); DLP (mGy.cm), BMI-based, 309.3 ± 127.5; IN-based, 230.6 ± 105.5; 25.4 % reduction (P < 0.001). Image-noise-based stratification of X-ray tube parameters for CTCA results in 32 % improvement in image quality and 25 % reduction in radiation dose compared with a BMI-based protocol. (orig.)

Dictionary-based image reconstruction for superresolution in integrated circuit imaging.

Science.gov (United States)

Cilingiroglu, T Berkin; Uyar, Aydan; Tuysuzoglu, Ahmet; Karl, W Clem; Konrad, Janusz; Goldberg, Bennett B; Ünlü, M Selim

2015-06-01

Resolution improvement through signal processing techniques for integrated circuit imaging is becoming more crucial as the rapid decrease in integrated circuit dimensions continues. Although there is a significant effort to push the limits of optical resolution for backside fault analysis through the use of solid immersion lenses, higher order laser beams, and beam apodization, signal processing techniques are required for additional improvement. In this work, we propose a sparse image reconstruction framework which couples overcomplete dictionary-based representation with a physics-based forward model to improve resolution and localization accuracy in high numerical aperture confocal microscopy systems for backside optical integrated circuit analysis. The effectiveness of the framework is demonstrated on experimental data.

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.

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.)

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.)

Content-based Image Hiding Method for Secure Network Biometric Verification

Directory of Open Access Journals (Sweden)

Xiangjiu Che

2011-08-01

Full Text Available For secure biometric verification, most existing methods embed biometric information directly into the cover image, but content correlation analysis between the biometric image and the cover image is often ignored. In this paper, we propose a novel biometric image hiding approach based on the content correlation analysis to protect the network-based transmitted image. By using principal component analysis (PCA, the content correlation between the biometric image and the cover image is firstly analyzed. Then based on particle swarm optimization (PSO algorithm, some regions of the cover image are selected to represent the biometric image, in which the cover image can carry partial content of the biometric image. As a result of the correlation analysis, the unrepresented part of the biometric image is embedded into the cover image by using the discrete wavelet transform (DWT. Combined with human visual system (HVS model, this approach makes the hiding result perceptually invisible. The extensive experimental results demonstrate that the proposed hiding approach is robust against some common frequency and geometric attacks; it also provides an effective protection for the secure biometric verification.

A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

OpenAIRE

Zhiqin Zhu; Guanqiu Qi; Yi Chai; Penghua Li

2017-01-01

In recent years, sparse representation approaches have been integrated into multi-focus image fusion methods. The fused images of sparse-representation-based image fusion methods show great performance. Constructing an informative dictionary is a key step for sparsity-based image fusion method. In order to ensure sufficient number of useful bases for sparse representation in the process of informative dictionary construction, image patches from all source images are classified into different ...

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.

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

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.

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

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.

The IMM Frontal Face Database

DEFF Research Database (Denmark)

Fagertun, Jens; Stegmann, Mikkel Bille

2005-01-01

This note describes a data set consisting of 120 annotated monocular images of 12 different frontal human faces. Points of correspondence are placed on each image so the data set can be readily used for building statistical models of shape. Format specifications and terms of use are also given...

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.

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...

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

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.

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

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.

Subspace-Based Holistic Registration for Low-Resolution Facial Images

Directory of Open Access Journals (Sweden)

Boom BJ

2010-01-01

Full Text Available Subspace-based holistic registration is introduced as an alternative to landmark-based face registration, which has a poor performance on low-resolution images, as obtained in camera surveillance applications. The proposed registration method finds the alignment by maximizing the similarity score between a probe and a gallery image. We use a novel probabilistic framework for both user-independent as well as user-specific face registration. The similarity is calculated using the probability that the face image is correctly aligned in a face subspace, but additionally we take the probability into account that the face is misaligned based on the residual error in the dimensions perpendicular to the face subspace. We perform extensive experiments on the FRGCv2 database to evaluate the impact that the face registration methods have on face recognition. Subspace-based holistic registration on low-resolution images can improve face recognition in comparison with landmark-based registration on high-resolution images. The performance of the tested face recognition methods after subspace-based holistic registration on a low-resolution version of the FRGC database is similar to that after manual registration.

A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

Directory of Open Access Journals (Sweden)

Zhiqin Zhu

2017-02-01

Full Text Available In recent years, sparse representation approaches have been integrated into multi-focus image fusion methods. The fused images of sparse-representation-based image fusion methods show great performance. Constructing an informative dictionary is a key step for sparsity-based image fusion method. In order to ensure sufficient number of useful bases for sparse representation in the process of informative dictionary construction, image patches from all source images are classified into different groups based on geometric similarities. The key information of each image-patch group is extracted by principle component analysis (PCA to build dictionary. According to the constructed dictionary, image patches are converted to sparse coefficients by simultaneous orthogonal matching pursuit (SOMP algorithm for representing the source multi-focus images. At last the sparse coefficients are fused by Max-L1 fusion rule and inverted to fused image. Due to the limitation of microscope, the fluorescence image cannot be fully focused. The proposed multi-focus image fusion solution is applied to fluorescence imaging area for generating all-in-focus images. The comparison experimentation results confirm the feasibility and effectiveness of the proposed multi-focus image fusion solution.

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...

Comparison of analyzer-based imaging computed tomography extraction algorithms and application to bone-cartilage imaging

International Nuclear Information System (INIS)

Diemoz, Paul C; Bravin, Alberto; Coan, Paola; Glaser, Christian

2010-01-01

In x-ray phase-contrast analyzer-based imaging, the contrast is provided by a combination of absorption, refraction and scattering effects. Several extraction algorithms, which attempt to separate and quantify these different physical contributions, have been proposed and applied. In a previous work, we presented a quantitative comparison of five among the most well-known extraction algorithms based on the geometrical optics approximation applied to planar images: diffraction-enhanced imaging (DEI), extended diffraction-enhanced imaging (E-DEI), generalized diffraction-enhanced imaging (G-DEI), multiple-image radiography (MIR) and Gaussian curve fitting (GCF). In this paper, we compare these algorithms in the case of the computed tomography (CT) modality. The extraction algorithms are applied to analyzer-based CT images of both plastic phantoms and biological samples (cartilage-on-bone cylinders). Absorption, refraction and scattering signals are derived. Results obtained with the different algorithms may vary greatly, especially in the case of large refraction angles. We show that ABI-CT extraction algorithms can provide an excellent tool to enhance the visualization of cartilage internal structures, which may find applications in a clinical context. Besides, by using the refraction images, the refractive index decrements for both the cartilage matrix and the cartilage cells have been estimated.

A 4DCT imaging-based breathing lung model with relative hysteresis

Energy Technology Data Exchange (ETDEWEB)

Miyawaki, Shinjiro; Choi, Sanghun [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A. [Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242 (United States)

2016-12-01

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

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

Unified framework for recognition, localization and mapping using wearable cameras.

Science.gov (United States)

Vázquez-Martín, Ricardo; Bandera, Antonio

2012-08-01

Monocular approaches to simultaneous localization and mapping (SLAM) have recently addressed with success the challenging problem of the fast computation of dense reconstructions from a single, moving camera. Thus, if these approaches initially relied on the detection of a reduced set of interest points to estimate the camera position and the map, they are currently able to reconstruct dense maps from a handheld camera while the camera coordinates are simultaneously computed. However, these maps of 3-dimensional points usually remain meaningless, that is, with no memorable items and without providing a way of encoding spatial relationships between objects and paths. In humans and mobile robotics, landmarks play a key role in the internalization of a spatial representation of an environment. They are memorable cues that can serve to define a region of the space or the location of other objects. In a topological representation of the space, landmarks can be identified and located according to its structural, perceptive or semantic significance and distinctiveness. But on the other hand, landmarks may be difficult to be located in a metric representation of the space. Restricted to the domain of visual landmarks, this work describes an approach where the map resulting from a point-based, monocular SLAM is annotated with the semantic information provided by a set of distinguished landmarks. Both features are obtained from the image. Hence, they can be linked by associating to each landmark all those point-based features that are superimposed to the landmark in a given image (key-frame). Visual landmarks will be obtained by means of an object-based, bottom-up attention mechanism, which will extract from the image a set of proto-objects. These proto-objects could not be always associated with natural objects, but they will typically constitute significant parts of these scene objects and can be appropriately annotated with semantic information. Moreover, they will be

Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

Directory of Open Access Journals (Sweden)

TAO Feixiang

2015-08-01

Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

High-speed photoacoustic imaging using an LED-based photoacoustic imaging system

Science.gov (United States)

Sato, Naoto; Kuniyil Ajith Singh, Mithun; Shigeta, Yusuke; Hanaoka, Takamitsu; Agano, Toshitaka

2018-02-01

Recently we developed a multispectral LED-based photoacoustic/ultrasound imaging system (AcousticX) and have been continuously working on its technical/functional improvements. AcousticX is a linear array ultrasound transducer (128 elements, 10 MHz)-based system in which LED arrays (selectable wavelengths, pulse repetition frequency: 4 kHz, pulse width: tunable from 40 - 100 ns) are fixed on both sides of the transducer to illuminate the tissue for photoacoustic imaging. The ultrasound/photoacoustic data from all 128 elements can be simultaneously acquired, processed and displayed. We already demonstrated our system's capability to perform photoacoustic/ultrasound imaging for dynamic imaging of the tissue at a frame rate of 10 Hz (for example to visualize the pulsation of arteries in vivo in human subjects). In this work, we present the development of a new high-speed imaging mode in AcousticX. In this mode, instead of toggling between ultrasound and photoacoustic measurements, it is possible to continuously acquire only photoacoustic data for 1.5 seconds with a time interval of 1 ms. With this improvement, we can record photoacoustic signals from the whole aperture (38 mm) at fast rate and can be reviewed later at different speeds for analyzing dynamic changes in the photoacoustic signals. We believe that AcousticX with this new high-speed mode opens up a feasible technical path for multiple dynamic studies, for example one which focus on imaging the response of voltage sensitive dyes. We envisage to improve the acquisition speed further in future for exploring ultra-high-speed applications.

INTEGRATION OF VIDEO IMAGES AND CAD WIREFRAMES FOR 3D OBJECT LOCALIZATION

Directory of Open Access Journals (Sweden)

R. A. Persad

2012-07-01

Full Text Available The tracking of moving objects from single images has received widespread attention in photogrammetric computer vision and considered to be at a state of maturity. This paper presents a model-driven solution for localizing moving objects detected from monocular, rotating and zooming video images in a 3D reference frame. To realize such a system, the recovery of 2D to 3D projection parameters is essential. Automatic estimation of these parameters is critical, particularly for pan-tilt-zoom (PTZ surveillance cameras where parameters change spontaneously upon camera motion. In this work, an algorithm for automated parameter retrieval is proposed. This is achieved by matching linear features between incoming images from video sequences and simple geometric 3D CAD wireframe models of man-made structures. The feature matching schema uses a hypothesis-verify optimization framework referred to as LR-RANSAC. This novel method improves the computational efficiency of the matching process in comparison to the standard RANSAC robust estimator. To demonstrate the applicability and performance of the method, experiments have been performed on indoor and outdoor image sequences under varying conditions with lighting changes and occlusions. Reliability of the matching algorithm has been analyzed by comparing the automatically determined camera parameters with ground truth (GT. Dependability of the retrieved parameters for 3D localization has also been assessed by comparing the difference between 3D positions of moving image objects estimated using the LR-RANSAC-derived parameters and those computed using GT parameters.

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.

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.

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

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.

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

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 ...

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.

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.

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.

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,

Graphene-based ultrasonic detector for photoacoustic imaging

Science.gov (United States)

Yang, Fan; Song, Wei; Zhang, Chonglei; Fang, Hui; Min, Changjun; Yuan, Xiaocong

2018-03-01

Taking advantage of optical absorption imaging contrast, photoacoustic imaging technology is able to map the volumetric distribution of the optical absorption properties within biological tissues. Unfortunately, traditional piezoceramics-based transducers used in most photoacoustic imaging setups have inadequate frequency response, resulting in both poor depth resolution and inaccurate quantification of the optical absorption information. Instead of the piezoelectric ultrasonic transducer, we develop a graphene-based optical sensor for detecting photoacoustic pressure. The refractive index in the coupling medium is modulated due to photoacoustic pressure perturbation, which creates the variation of the polarization-sensitive optical absorption property of the graphene. As a result, the photoacoustic detection is realized through recording the reflectance intensity difference of polarization light. The graphene-based detector process an estimated noise-equivalentpressure (NEP) sensitivity of 550 Pa over 20-MHz bandwidth with a nearby linear pressure response from 11.0 kPa to 53.0 kPa. Further, a graphene-based photoacoustic microscopy is built, and non-invasively reveals the microvascular anatomy in mouse ears label-freely.

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.

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.

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.

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.

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

Image dissimilarity-based quantification of lung disease from CT

DEFF Research Database (Denmark)

Sørensen, Lauge; Loog, Marco; Lo, Pechin Chien Pau

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...

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.

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.

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.

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.

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

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.

Pose Self-Measurement of Noncooperative Spacecraft Based on Solar Panel Triangle Structure

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Jingzhou Song

2015-01-01

Full Text Available Aiming at the recognition and location of noncooperative spacecraft, this paper presents a monocular vision pose measurement method based on solar triangle structure. First of all, an autonomous recognition algorithm of feature structure based on sliding window Hough transformation (SWHT and inscribed circle of a triangle is proposed, and the image coordinates of feature points on the triangle can be obtained relying on this algorithm, combined with the P4P algorithm and the structure of spacecraft, calculating the relative pose of target expressed by rotation and translation matrix. The whole algorithm can be loaded into the prewritten onboard program, which will get the autocomplete feature structure extraction and relative pose measurement without human intervention, and this method does not need to mount any markers on the target. Then compare the measured values with the accurate value of the laser tracker, so that a conclusion can be drawn that the maximum position error is lower than 5% and the rotation error is lower than 4%, which meets the requirements of noncooperative spacecraft’s pose measurement for observations, tracking, and docking in the final rendezvous phase.

Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement

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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.

LINE-BASED MULTI-IMAGE MATCHING FOR FAÇADE RECONSTRUCTION

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T. A. Teo

2012-07-01

Full Text Available This research integrates existing LOD 2 building models and multiple close-range images for façade structural lines extraction. The major works are orientation determination and multiple image matching. In the orientation determination, Speeded Up Robust Features (SURF is applied to extract tie points automatically. Then, tie points and control points are combined for block adjustment. An object-based multi-images matching is proposed to extract the façade structural lines. The 2D lines in image space are extracted by Canny operator followed by Hough transform. The role of LOD 2 building models is to correct the tilt displacement of image from different views. The wall of LOD 2 model is also used to generate hypothesis planes for similarity measurement. Finally, average normalized cross correlation is calculated to obtain the best location in object space. The test images are acquired by a nonmetric camera Nikon D2X. The total number of image is 33. The experimental results indicate that the accuracy of orientation determination is about 1 pixel from 2515 tie points and 4 control points. It also indicates that line-based matching is more flexible than point-based matching.

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.

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

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.

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)

An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

Directory of Open Access Journals (Sweden)

Guanqiu Qi

2017-10-01

Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization

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Minxiang Liu

2013-01-01

Full Text Available We present a novel feature-level data fusion method for autonomous localization in an inactive multiple reference unknown indoor environment. Since monocular sensors cannot provide the depth information directly, the proposed method incorporates the edge information of images from a camera with homologous depth information received from an infrared sensor. Real-time experimental results demonstrate that the accuracies of position and orientation are greatly improved by using the proposed fusion method in an unknown complex indoor environment. Compared to monocular localization, the proposed method is found to have up to 70 percent improvement in accuracy.

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

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

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.

Experience-independent development of the hamster circadian visual system.

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August Kampf-Lassin

2011-04-01

Full Text Available Experience-dependent functional plasticity is a hallmark of the primary visual system, but it is not known if analogous mechanisms govern development of the circadian visual system. Here we investigated molecular, anatomical, and behavioral consequences of complete monocular light deprivation during extended intervals of postnatal development in Syrian hamsters. Hamsters were raised in constant darkness and opaque contact lenses were applied shortly after eye opening and prior to the introduction of a light-dark cycle. In adulthood, previously-occluded eyes were challenged with visual stimuli. Whereas image-formation and motion-detection were markedly impaired by monocular occlusion, neither entrainment to a light-dark cycle, nor phase-resetting responses to shifts in the light-dark cycle were affected by prior monocular deprivation. Cholera toxin-b subunit fluorescent tract-tracing revealed that in monocularly-deprived hamsters the density of fibers projecting from the retina to the suprachiasmatic nucleus (SCN was comparable regardless of whether such fibers originated from occluded or exposed eyes. In addition, long-term monocular deprivation did not attenuate light-induced c-Fos expression in the SCN. Thus, in contrast to the thalamocortical projections of the primary visual system, retinohypothalamic projections terminating in the SCN develop into normal adult patterns and mediate circadian responses to light largely independent of light experience during development. The data identify a categorical difference in the requirement for light input during postnatal development between circadian and non-circadian visual systems.

Radionuclide-Based Cancer Imaging Targeting the Carcinoembryonic Antigen

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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”.

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

Robust obstacle detection for unmanned surface vehicles

Science.gov (United States)

Qin, Yueming; Zhang, Xiuzhi

2018-03-01

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Pathfinder: multiresolution region-based searching of pathology images using IRM.

OpenAIRE

Wang, J. Z.

2000-01-01

The fast growth of digitized pathology slides has created great challenges in research on image database retrieval. The prevalent retrieval technique involves human-supplied text annotations to describe slide contents. These pathology images typically have very high resolution, making it difficult to search based on image content. In this paper, we present Pathfinder, an efficient multiresolution region-based searching system for high-resolution pathology image libraries. The system uses wave...

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.

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.

Recovering stereo vision by squashing virtual bugs in a virtual reality environment.

Science.gov (United States)

Vedamurthy, Indu; Knill, David C; Huang, Samuel J; Yung, Amanda; Ding, Jian; Kwon, Oh-Sang; Bavelier, Daphne; Levi, Dennis M

2016-06-19

Stereopsis is the rich impression of three-dimensionality, based on binocular disparity-the differences between the two retinal images of the same world. However, a substantial proportion of the population is stereo-deficient, and relies mostly on monocular cues to judge the relative depth or distance of objects in the environment. Here we trained adults who were stereo blind or stereo-deficient owing to strabismus and/or amblyopia in a natural visuomotor task-a 'bug squashing' game-in a virtual reality environment. The subjects' task was to squash a virtual dichoptic bug on a slanted surface, by hitting it with a physical cylinder they held in their hand. The perceived surface slant was determined by monocular texture and stereoscopic cues, with these cues being either consistent or in conflict, allowing us to track the relative weighting of monocular versus stereoscopic cues as training in the task progressed. Following training most participants showed greater reliance on stereoscopic cues, reduced suppression and improved stereoacuity. Importantly, the training-induced changes in relative stereo weights were significant predictors of the improvements in stereoacuity. We conclude that some adults deprived of normal binocular vision and insensitive to the disparity information can, with appropriate experience, recover access to more reliable stereoscopic information.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

Recovering stereo vision by squashing virtual bugs in a virtual reality environment

Science.gov (United States)

Vedamurthy, Indu; Knill, David C.; Huang, Samuel J.; Yung, Amanda; Ding, Jian; Kwon, Oh-Sang; Bavelier, Daphne

2016-01-01

Stereopsis is the rich impression of three-dimensionality, based on binocular disparity—the differences between the two retinal images of the same world. However, a substantial proportion of the population is stereo-deficient, and relies mostly on monocular cues to judge the relative depth or distance of objects in the environment. Here we trained adults who were stereo blind or stereo-deficient owing to strabismus and/or amblyopia in a natural visuomotor task—a ‘bug squashing’ game—in a virtual reality environment. The subjects' task was to squash a virtual dichoptic bug on a slanted surface, by hitting it with a physical cylinder they held in their hand. The perceived surface slant was determined by monocular texture and stereoscopic cues, with these cues being either consistent or in conflict, allowing us to track the relative weighting of monocular versus stereoscopic cues as training in the task progressed. Following training most participants showed greater reliance on stereoscopic cues, reduced suppression and improved stereoacuity. Importantly, the training-induced changes in relative stereo weights were significant predictors of the improvements in stereoacuity. We conclude that some adults deprived of normal binocular vision and insensitive to the disparity information can, with appropriate experience, recover access to more reliable stereoscopic information. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269607

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.

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.

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.

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.

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.

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.

A Reliable Image Watermarking Scheme Based on Redistributed Image Normalization and SVD

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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.

Defogging of road images using gain coefficient-based trilateral filter

Science.gov (United States)

Singh, Dilbag; Kumar, Vijay

2018-01-01

Poor weather conditions are responsible for most of the road accidents year in and year out. Poor weather conditions, such as fog, degrade the visibility of objects. Thus, it becomes difficult for drivers to identify the vehicles in a foggy environment. The dark channel prior (DCP)-based defogging techniques have been found to be an efficient way to remove fog from road images. However, it produces poor results when image objects are inherently similar to airlight and no shadow is cast on them. To eliminate this problem, a modified restoration model-based DCP is developed to remove the fog from road images. The transmission map is also refined by developing a gain coefficient-based trilateral filter. Thus, the proposed technique has an ability to remove fog from road images in an effective manner. The proposed technique is compared with seven well-known defogging techniques on two benchmark foggy images datasets and five real-time foggy images. The experimental results demonstrate that the proposed approach is able to remove the different types of fog from roadside images as well as significantly improve the image's visibility. It also reveals that the restored image has little or no artifacts.

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.

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.

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.

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

FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT

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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.

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).

Brain medical image diagnosis based on corners with importance-values.

Science.gov (United States)

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

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

Knowledge-based analysis and understanding of 3D medical images

International Nuclear Information System (INIS)

Dhawan, A.P.; Juvvadi, S.

1988-01-01

The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. The authors objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest

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...

Imaged-Based Visual Servo Control for a VTOL Aircraft

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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.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing; Wang, B.; Lubineau, Gilles; Moussawi, Ali

2015-01-01

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing

2015-02-12

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Parallel content-based sub-image retrieval using hierarchical searching.

Science.gov (United States)

Yang, Lin; Qi, Xin; Xing, Fuyong; Kurc, Tahsin; Saltz, Joel; Foran, David J

2014-04-01

The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/.

Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation

International Nuclear Information System (INIS)

Wang, Yan; Zhou, Jiliu; Zhang, Pei; An, Le; Ma, Guangkai; Kang, Jiayin; Shi, Feng; Shen, Dinggang; Wu, Xi; Lalush, David S; Lin, Weili

2016-01-01

Positron emission tomography (PET) has been widely used in clinical diagnosis for diseases and disorders. To obtain high-quality PET images requires a standard-dose radionuclide (tracer) injection into the human body, which inevitably increases risk of radiation exposure. One possible solution to this problem is to predict the standard-dose PET image from its low-dose counterpart and its corresponding multimodal magnetic resonance (MR) images. Inspired by the success of patch-based sparse representation (SR) in super-resolution image reconstruction, we propose a mapping-based SR (m-SR) framework for standard-dose PET image prediction. Compared with the conventional patch-based SR, our method uses a mapping strategy to ensure that the sparse coefficients, estimated from the multimodal MR images and low-dose PET image, can be applied directly to the prediction of standard-dose PET image. As the mapping between multimodal MR images (or low-dose PET image) and standard-dose PET images can be particularly complex, one step of mapping is often insufficient. To this end, an incremental refinement framework is therefore proposed. Specifically, the predicted standard-dose PET image is further mapped to the target standard-dose PET image, and then the SR is performed again to predict a new standard-dose PET image. This procedure can be repeated for prediction refinement of the iterations. Also, a patch selection based dictionary construction method is further used to speed up the prediction process. The proposed method is validated on a human brain dataset. The experimental results show that our method can outperform benchmark methods in both qualitative and quantitative measures. (paper)

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.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Science.gov (United States)

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Directory of Open Access Journals (Sweden)

Liyun Zhuang

2017-01-01

Full Text Available This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE, which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE. Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance.

Science.gov (United States)

Zhuang, Liyun; Guan, Yepeng

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

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.

Task-based statistical image reconstruction for high-quality cone-beam CT

Science.gov (United States)

Dang, Hao; Webster Stayman, J.; Xu, Jennifer; Zbijewski, Wojciech; Sisniega, Alejandro; Mow, Michael; Wang, Xiaohui; Foos, David H.; Aygun, Nafi; Koliatsos, Vassilis E.; Siewerdsen, Jeffrey H.

2017-11-01

Task-based analysis of medical imaging performance underlies many ongoing efforts in the development of new imaging systems. In statistical image reconstruction, regularization is often formulated in terms to encourage smoothness and/or sharpness (e.g. a linear, quadratic, or Huber penalty) but without explicit formulation of the task. We propose an alternative regularization approach in which a spatially varying penalty is determined that maximizes task-based imaging performance at every location in a 3D image. We apply the method to model-based image reconstruction (MBIR—viz., penalized weighted least-squares, PWLS) in cone-beam CT (CBCT) of the head, focusing on the task of detecting a small, low-contrast intracranial hemorrhage (ICH), and we test the performance of the algorithm in the context of a recently developed CBCT prototype for point-of-care imaging of brain injury. Theoretical predictions of local spatial resolution and noise are computed via an optimization by which regularization (specifically, the quadratic penalty strength) is allowed to vary throughout the image to maximize local task-based detectability index ({{d}\\prime} ). Simulation studies and test-bench experiments were performed using an anthropomorphic head phantom. Three PWLS implementations were tested: conventional (constant) penalty; a certainty-based penalty derived to enforce constant point-spread function, PSF; and the task-based penalty derived to maximize local detectability at each location. Conventional (constant) regularization exhibited a fairly strong degree of spatial variation in {{d}\\prime} , and the certainty-based method achieved uniform PSF, but each exhibited a reduction in detectability compared to the task-based method, which improved detectability up to ~15%. The improvement was strongest in areas of high attenuation (skull base), where the conventional and certainty-based methods tended to over-smooth the data. The task-driven reconstruction method presents a

A simple method for detecting tumor in T2-weighted MRI brain images. An image-based analysis

International Nuclear Information System (INIS)

Lau, Phooi-Yee; Ozawa, Shinji

2006-01-01

The objective of this paper is to present a decision support system which uses a computer-based procedure to detect tumor blocks or lesions in digitized medical images. The authors developed a simple method with a low computation effort to detect tumors on T2-weighted Magnetic Resonance Imaging (MRI) brain images, focusing on the connection between the spatial pixel value and tumor properties from four different perspectives: cases having minuscule differences between two images using a fixed block-based method, tumor shape and size using the edge and binary images, tumor properties based on texture values using spatial pixel intensity distribution controlled by a global discriminate value, and the occurrence of content-specific tumor pixel for threshold images. Measurements of the following medical datasets were performed: different time interval images, and different brain disease images on single and multiple slice images. Experimental results have revealed that our proposed technique incurred an overall error smaller than those in other proposed methods. In particular, the proposed method allowed decrements of false alarm and missed alarm errors, which demonstrate the effectiveness of our proposed technique. In this paper, we also present a prototype system, known as PCB, to evaluate the performance of the proposed methods by actual experiments, comparing the detection accuracy and system performance. (author)

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)

Hyperspectral image compressing using wavelet-based method

Science.gov (United States)

Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

2017-10-01

Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone

Directory of Open Access Journals (Sweden)

Rifat Zaman

2017-02-01

Full Text Available We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

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.)

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

A novel multiphoton microscopy images segmentation method based on superpixel and watershed.

Science.gov (United States)

Wu, Weilin; Lin, Jinyong; Wang, Shu; Li, Yan; Liu, Mingyu; Liu, Gaoqiang; Cai, Jianyong; Chen, Guannan; Chen, Rong

2017-04-01

Multiphoton microscopy (MPM) imaging technique based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) shows fantastic performance for biological imaging. The automatic segmentation of cellular architectural properties for biomedical diagnosis based on MPM images is still a challenging issue. A novel multiphoton microscopy images segmentation method based on superpixels and watershed (MSW) is presented here to provide good segmentation results for MPM images. The proposed method uses SLIC superpixels instead of pixels to analyze MPM images for the first time. The superpixels segmentation based on a new distance metric combined with spatial, CIE Lab color space and phase congruency features, divides the images into patches which keep the details of the cell boundaries. Then the superpixels are used to reconstruct new images by defining an average value of superpixels as image pixels intensity level. Finally, the marker-controlled watershed is utilized to segment the cell boundaries from the reconstructed images. Experimental results show that cellular boundaries can be extracted from MPM images by MSW with higher accuracy and robustness. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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...

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.

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.

Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

International Nuclear Information System (INIS)

Morrow, Natalya V.; Lawton, Colleen A.; Qi, X. Sharon; Li, X. Allen

2012-01-01

Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

Energy Technology Data Exchange (ETDEWEB)

Morrow, Natalya V.; Lawton, Colleen A. [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin (United States); Qi, X. Sharon [Department of Radiation Oncology, University of Colorado Denver, Denver, Colorado (United States); Li, X. Allen, E-mail: ali@mcw.edu [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin (United States)

2012-04-01

Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

Space-based infrared sensors of space target imaging effect analysis

Science.gov (United States)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

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.

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.

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.

Shape-based interpolation of multidimensional grey-level images

International Nuclear Information System (INIS)

Grevera, G.J.; Udupa, J.K.

1996-01-01

Shape-based interpolation as applied to binary images causes the interpolation process to be influenced by the shape of the object. It accomplishes this by first applying a distance transform to the data. This results in the creation of a grey-level data set in which the value at each point represents the minimum distance from that point to the surface of the object. (By convention, points inside the object are assigned positive values; points outside are assigned negative values.) This distance transformed data set is then interpolated using linear or higher-order interpolation and is then thresholded at a distance value of zero to produce the interpolated binary data set. In this paper, the authors describe a new method that extends shape-based interpolation to grey-level input data sets. This generalization consists of first lifting the n-dimensional (n-D) image data to represent it as a surface, or equivalently as a binary image, in an (n + 1)-dimensional [(n + 1)-D] space. The binary shape-based method is then applied to this image to create an (n + 1)-D binary interpolated image. Finally, this image is collapsed (inverse of lifting) to create the n-D interpolated grey-level data set. The authors have conducted several evaluation studies involving patient computed tomography (CT) and magnetic resonance (MR) data as well as mathematical phantoms. They all indicate that the new method produces more accurate results than commonly used grey-level linear interpolation methods, although at the cost of increased computation

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).

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