Dynamic Parameter Identification of Hydrodynamic Bearing-Rotor System

Directory of Open Access Journals (Sweden)

Zhiqiang Song

2015-01-01

Full Text Available A new method called modal parameter genetic time domain identification was employed to study the characteristics of the bearing-rotor system. A multifrequency signal decomposition technology to identify the main components of the measured signal and reject the image mode produced by noise has been used. The first- and second-order natural frequency and damping ratios of the shaft system are identified. Furthermore, because of the deficiency of the traditional least square method, a new genetic identification method to identify the bearing dynamic characteristic parameters has been proposed. The method has been effective albeit with few testing points and operation cases. The derivation of oil-film dynamic coefficients could also provide a basis for shaft system natural vibration characteristic and vibration response analysis. Using the identified dynamic coefficients as the supporting condition, the shaft system modal characteristics were studied. The calculated first- and second-order natural frequencies match quite well those obtained from the modal parameter identification. It was proved that the modal parameter and physical parameter identification methods utilized in this paper are reasonable.

Effects of image enhancement on reliability of landmark identification in digital cephalometry

Directory of Open Access Journals (Sweden)

M Oshagh

2013-01-01

Full Text Available Introduction: Although digital cephalometric radiography is gaining popularity in orthodontic practice, the most important source of error in its tracing is uncertainty in landmark identification. Therefore, efforts to improve accuracy in landmark identification were directed primarily toward the improvement in image quality. One of the more useful techniques of this process involves digital image enhancement which can increase overall visual quality of image, but this does not necessarily mean a better identification of landmarks. The purpose of this study was to evaluate the effectiveness of digital image enhancements on reliability of landmark identification. Materials and Methods: Fifteen common landmarks including 10 skeletal and 5 soft tissues were selected on the cephalograms of 20 randomly selected patients, prepared in Natural Head Position (NHP. Two observers (orthodontists identified landmarks on the 20 original photostimulable phosphor (PSP digital cephalogram images and 20 enhanced digital images twice with an intervening time interval of at least 4 weeks. The x and y coordinates were further analyzed to evaluate the pattern of recording differences in horizontal and vertical directions. Reliability of landmarks identification was analyzed by paired t test. Results: There was a significant difference between original and enhanced digital images in terms of reliability of points Ar and N in vertical and horizontal dimensions, and enhanced images were significantly more reliable than original images. Identification of A point, Pogonion and Pronasal points, in vertical dimension of enhanced images was significantly more reliable than original ones. Reliability of Menton point identification in horizontal dimension was significantly more in enhanced images than original ones. Conclusion: Direct digital image enhancement by altering brightness and contrast can increase reliability of some landmark identification and this may lead to more

Multipurpose Hyperspectral Imaging System

Science.gov (United States)

Mao, Chengye; Smith, David; Lanoue, Mark A.; Poole, Gavin H.; Heitschmidt, Jerry; Martinez, Luis; Windham, William A.; Lawrence, Kurt C.; Park, Bosoon

2005-01-01

A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

21 CFR 892.1560 - Ultrasonic pulsed echo imaging system.

Science.gov (United States)

2010-04-01

... system. (a) Identification. An ultrasonic pulsed echo imaging system is a device intended to project a... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Ultrasonic pulsed echo imaging system. 892.1560... receiver. This generic type of device may include signal analysis and display equipment, patient and...

Fieldable Nuclear Material Identification System

International Nuclear Information System (INIS)

Radle, James E.; Archer, Daniel E.; Carter, Robert J.; Mullens, James Allen; Mihalczo, John T.; Britton, Charles L. Jr.; Lind, Randall F.; Wright, Michael C.

2010-01-01

The Fieldable Nuclear Material Identification System (FNMIS), funded by the NA-241 Office of Dismantlement and Transparency, provides information to determine the material attributes and identity of heavily shielded nuclear objects. This information will provide future treaty participants with verifiable information required by the treaty regime. The neutron interrogation technology uses a combination of information from induced fission neutron radiation and transmitted neutron imaging information to provide high confidence that the shielded item is consistent with the host's declaration. The combination of material identification information and the shape and configuration of the item are very difficult to spoof. When used at various points in the warhead dismantlement sequence, the information complimented by tags and seals can be used to track subassembly and piece part information as the disassembly occurs. The neutron transmission imaging has been developed during the last seven years and the signature analysis over the last several decades. The FNMIS is the culmination of the effort to put the technology in a usable configuration for potential treaty verification purposes.

An online ID identification system for liquefied-gas cylinder plant

Science.gov (United States)

He, Jin; Ding, Zhenwen; Han, Lei; Zhang, Hao

2017-11-01

An automatic ID identification system for gas cylinders' online production was developed based on the production conditions and requirements of the Technical Committee for Standardization of Gas Cylinders. A cylinder ID image acquisition system was designed to improve the image contrast of ID regions on gas cylinders against the background. Then the ID digits region was located by the CNN template matching algorithm. Following that, an adaptive threshold method based on the analysis of local average grey value and standard deviation was proposed to overcome defects of non-uniform background in the segmentation results. To improve the single digit identification accuracy, two BP neural networks were trained respectively for the identification of all digits and the easily confusable digits. If the single digit was classified as one of confusable digits by the former BP neural network, it was further tested by the later one, and the later result was taken as the final identification result of this single digit. At last, the majority voting was adopted to decide the final identification result for the 6-digit cylinder ID. The developed system was installed on a production line of a liquefied-petroleum-gas cylinder plant and worked in parallel with the existing weighing step on the line. Through the field test, the correct identification rate for single ID digit was 94.73%, and none of the tested 2000 cylinder ID was misclassified through the majority voting.

Facial identification in very low-resolution images simulating prosthetic vision.

Science.gov (United States)

Chang, M H; Kim, H S; Shin, J H; Park, K S

2012-08-01

Familiar facial identification is important to blind or visually impaired patients and can be achieved using a retinal prosthesis. Nevertheless, there are limitations in delivering the facial images with a resolution sufficient to distinguish facial features, such as eyes and nose, through multichannel electrode arrays used in current visual prostheses. This study verifies the feasibility of familiar facial identification under low-resolution prosthetic vision and proposes an edge-enhancement method to deliver more visual information that is of higher quality. We first generated a contrast-enhanced image and an edge image by applying the Sobel edge detector and blocked each of them by averaging. Then, we subtracted the blocked edge image from the blocked contrast-enhanced image and produced a pixelized image imitating an array of phosphenes. Before subtraction, every gray value of the edge images was weighted as 50% (mode 2), 75% (mode 3) and 100% (mode 4). In mode 1, the facial image was blocked and pixelized with no further processing. The most successful identification was achieved with mode 3 at every resolution in terms of identification index, which covers both accuracy and correct response time. We also found that the subjects recognized a distinctive face especially more accurately and faster than the other given facial images even under low-resolution prosthetic vision. Every subject could identify familiar faces even in very low-resolution images. And the proposed edge-enhancement method seemed to contribute to intermediate-stage visual prostheses.

Automated dental identification system: An aid to forensic odontology

Directory of Open Access Journals (Sweden)

Parvathi Devi

2011-01-01

Full Text Available Automated dental identification system is computer-aided software for the postmortem identification of deceased individuals based on dental characteristics specifically radiographs. This system is receiving increased attention because of the large number of victims encountered in the mass disasters and it is 90% more time saving and accurate than the conventional radiographic methods. This technique is based on the intensity of the overall region of tooth image and therefore it does not necessitate the presence of sharp boundary between the teeth. It provides automated search and matching capabilities for digitized radiographs and photographic dental images and compares the teeth present in multiple digitized dental records in order to access their similarity. This paper highlights the functionality of its components and techniques used in realizing these components.

Implementation of Minutiae Based Fingerprint Identification System Using Crossing Number Concept

Directory of Open Access Journals (Sweden)

Atul S. CHAUDHARI

2014-01-01

Full Text Available Biometric system is essentially a pattern recognition system which recognizes a person by determining the authenticity of a specific physiological (e.g., fingerprints, face, retina, iris or behavioral (e.g., gait, signature characteristic possessed by that person. Among all the presently employed biometric techniques, fingerprint identification systems have received the most attention due to the long history of fingerprints and its extensive use in forensics. Fingerprint is reliable biometric characteristic as it is unique and persistence. Fingerprint is the pattern of ridges and valleys on the surface of fingertip. However, recognizing fingerprints in poor quality images is still a very complex job, so the fingerprint image must be preprocessed before matching. It is very difficult to extract fingerprint features directly from gray scale fingerprint image. In this paper we have proposed the system which uses minutiae based matching algorithm for fingerprint identification. There are three main phases in proposed algorithm. First phase enhance the input fingerprint image by preprocessing it. The enhanced fingerprint image is converted into thinned binary image and then minutiae are extracted by using Crossing Number Concept in second phase. Third stage compares input fingerprint image (after preprocessing and minutiae extraction with fingerprint images enrolled in database and makes decision whether the input fingerprint is matched with the fingerprint stored in database or not.

Use of Multispectral Imaging in Varietal Identification of Tomato

DEFF Research Database (Denmark)

Shrestha, Santosh; Deleuran, Lise Christina; Olesen, Merete Halkjær

2015-01-01

Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... obtained provide an opportunity of using multispectral imaging technology as a primary tool in a scientific community for identification/discrimination of plant varieties in regard to genetic purity and plant variety protection/registration.......Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... cultivars to study parents and offspring relationship and varietal identification respectively. Normalized canonical discriminant analysis (nCDA) and principal component analysis (PCA) were used to analyze and compare the results for parents and offspring study. Both the results showed clear discrimination...

A Gender Identification System for Customers in a Shop Using Infrared Area Scanners

Science.gov (United States)

Tajima, Takuya; Kimura, Haruhiko; Abe, Takehiko; Abe, Koji; Nakamoto, Yoshinori

Information about customers in shops plays an important role in marketing analysis. Currently, in convenience stores and supermarkets, the identification of customer's gender is examined by clerks. On the other hand, gender identification systems using camera images are investigated. However, these systems have a problem of invading human privacies in identifying attributes of customers. The proposed system identifies gender by using infrared area scanners and Bayesian network. In the proposed system, since infrared area scanners do not take customers' images directly, invasion of privacies are not occurred. The proposed method uses three parameters of height, walking speed and pace for humans. In general, it is shown that these parameters have factors of sexual distinction in humans, and Bayesian network is designed with these three parameters. The proposed method resolves the existent problems of restricting the locations where the systems are set and invading human privacies. Experimental results using data obtained from 450 people show that the identification rate for the proposed method was 91.3% on the average of both of male and female identifications.

21 CFR 892.1650 - Image-intensified fluoroscopic x-ray system.

Science.gov (United States)

2010-04-01

... fluoroscopic x-ray system. (a) Identification. An image-intensified fluoroscopic x-ray system is a device... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Image-intensified fluoroscopic x-ray system. 892... equipment, patient and equipment supports, component parts, and accessories. (b) Classification. Class II...

The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

Science.gov (United States)

Kao, Meng-Chun; Ting, Chien-Kun; Kuo, Wen-Chuan

2018-02-01

Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.

Superpixel segmentation and pigment identification of colored relics based on visible spectral image

Science.gov (United States)

Li, Junfeng; Wan, Xiaoxia

2018-01-01

To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution.

Is it possible to eliminate patient identification errors in medical imaging?

Science.gov (United States)

Danaher, Luke A; Howells, Joan; Holmes, Penny; Scally, Peter

2011-08-01

The aim of this article is to review a system that validates and documents the process of ensuring the correct patient, correct site and side, and correct procedure (commonly referred to as the 3 C's) within medical imaging. A 4-step patient identification and procedure matching process was developed using health care and aviation models. The process was established in medical imaging departments after a successful interventional radiology pilot program. The success of the project was evaluated using compliance audit data, incident reporting data before and after the implementation of the process, and a staff satisfaction survey. There was 95% to 100% verification of site and side and 100% verification of correct patient, procedure, and consent. Correct patient data and side markers were present in 82% to 95% of cases. The number of incidents before and after the implementation of the 3 C's was difficult to assess because of a change in reporting systems and incident underreporting. More incidents are being reported, particularly "near misses." All near misses were related to incorrect patient identification stickers being placed on request forms. The majority of staff members surveyed found the process easy (55.8%), quick (47.7%), relevant (51.7%), and useful (60.9%). Although identification error is difficult to eliminate, practical initiatives can engender significant systems improvement in complex health care environments. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Image De-Identification Methods for Clinical Research in the XDS Environment

NARCIS (Netherlands)

Aryanto, K. Y. E.; van Kernebeek, G.; Berendsen, B.; Oudkerk, M.; van Ooijen, P. M. A.

To investigate possible de-identification methodologies within the Cross-Enterprise Document Sharing for imaging (XDS-I) environment in order to provide strengthened support for image data exchange as part of clinical research projects. De-identification, using anonymization or pseudonymization, is

Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications.

Science.gov (United States)

Singh, Anushikha; Dutta, Malay Kishore; Sharma, Dilip Kumar

2016-10-01

Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Biased lineup instructions and face identification from video images.

Science.gov (United States)

Thompson, W Burt; Johnson, Jaime

2008-01-01

Previous eyewitness memory research has shown that biased lineup instructions reduce identification accuracy, primarily by increasing false-positive identifications in target-absent lineups. Because some attempts at identification do not rely on a witness's memory of the perpetrator but instead involve matching photos to images on surveillance video, the authors investigated the effects of biased instructions on identification accuracy in a matching task. In Experiment 1, biased instructions did not affect the overall accuracy of participants who used video images as an identification aid, but nearly all correct decisions occurred with target-present photo spreads. Both biased and unbiased instructions resulted in high false-positive rates. In Experiment 2, which focused on video-photo matching accuracy with target-absent photo spreads, unbiased instructions led to more correct responses (i.e., fewer false positives). These findings suggest that investigators should not relax precautions against biased instructions when people attempt to match photos to an unfamiliar person recorded on video.

Optical Imaging Sensors and Systems for Homeland Security Applications

CERN Document Server

Javidi, Bahram

2006-01-01

Optical and photonic systems and devices have significant potential for homeland security. Optical Imaging Sensors and Systems for Homeland Security Applications presents original and significant technical contributions from leaders of industry, government, and academia in the field of optical and photonic sensors, systems and devices for detection, identification, prevention, sensing, security, verification and anti-counterfeiting. The chapters have recent and technically significant results, ample illustrations, figures, and key references. This book is intended for engineers and scientists in the relevant fields, graduate students, industry managers, university professors, government managers, and policy makers. Advanced Sciences and Technologies for Security Applications focuses on research monographs in the areas of -Recognition and identification (including optical imaging, biometrics, authentication, verification, and smart surveillance systems) -Biological and chemical threat detection (including bios...

Statistical analysis of texture in trunk images for biometric identification of tree species.

Science.gov (United States)

Bressane, Adriano; Roveda, José A F; Martins, Antônio C G

2015-04-01

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

An open source toolkit for medical imaging de-identification

International Nuclear Information System (INIS)

Rodriguez Gonzalez, David; Carpenter, Trevor; Wardlaw, Joanna; Hemert, Jano I. van

2010-01-01

Medical imaging acquired for clinical purposes can have several legitimate secondary uses in research projects and teaching libraries. No commonly accepted solution for anonymising these images exists because the amount of personal data that should be preserved varies case by case. Our objective is to provide a flexible mechanism for anonymising Digital Imaging and Communications in Medicine (DICOM) data that meets the requirements for deployment in multicentre trials. We reviewed our current de-identification practices and defined the relevant use cases to extract the requirements for the de-identification process. We then used these requirements in the design and implementation of the toolkit. Finally, we tested the toolkit taking as a reference those requirements, including a multicentre deployment. The toolkit successfully anonymised DICOM data from various sources. Furthermore, it was shown that it could forward anonymous data to remote destinations, remove burned-in annotations, and add tracking information to the header. The toolkit also implements the DICOM standard confidentiality mechanism. A DICOM de-identification toolkit that facilitates the enforcement of privacy policies was developed. It is highly extensible, provides the necessary flexibility to account for different de-identification requirements and has a low adoption barrier for new users. (orig.)

White blood cells identification system based on convolutional deep neural learning networks.

Science.gov (United States)

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

21 CFR 892.1660 - Non-image-intensified fluoroscopic x-ray system.

Science.gov (United States)

2010-04-01

... fluoroscopic x-ray system. (a) Identification. A non-image-intensified fluoroscopic x-ray system is a device... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Non-image-intensified fluoroscopic x-ray system... display equipment, patient and equipment supports, component parts, and accessories. (b) Classification...

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

Science.gov (United States)

Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

2017-07-01

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

Fuzzy-Rule-Based Object Identification Methodology for NAVI System

Directory of Open Access Journals (Sweden)

Yaacob Sazali

2005-01-01

Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

Fuzzy-Rule-Based Object Identification Methodology for NAVI System

Science.gov (United States)

Nagarajan, R.; Sainarayanan, G.; Yaacob, Sazali; Porle, Rosalyn R.

2005-12-01

We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

Contribute to quantitative identification of casting defects based on computer analysis of X-ray images

Directory of Open Access Journals (Sweden)

Z. Ignaszak

2007-12-01

Full Text Available The forecast of structure and properties of casting is based on results of computer simulation of physical processes which are carried out during the casting processes. For the effective using of simulation system it is necessary to validate mathematica-physical models describing process of casting formation and the creation of local discontinues, witch determinate the casting properties.In the paper the proposition for quantitative validation of VP system using solidification casting defects by information sources of II group (methods of NDT was introduced. It was named the VP/RT validation (virtual prototyping/radiographic testing validation. Nowadays identification of casting defects noticeable on X-ray images bases on comparison of X-ray image of casting with relates to the ASTM. The results of this comparison are often not conclusive because based on operator’s subjective assessment. In the paper the system of quantitative identification of iron casting defects on X-ray images and classification this defects to ASTM class is presented. The methods of pattern recognition and machine learning were applied.

Snapshot spectral and polarimetric imaging; target identification with multispectral video

Science.gov (United States)

Bartlett, Brent D.; Rodriguez, Mikel D.

2013-05-01

As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

Integrating two spectral imaging systems in an automated mineralogy application

CSIR Research Space (South Africa)

Harris, D

2009-11-01

Full Text Available is treated in batches, with trays of mono-layered material presented to various imaging systems. The identification of target grains is achieved by means of spectral imaging in two wavelength bands (Visible, and Long Wave Infrared). Target grains...

Biometric identification using infrared dorsum hand vein images

Directory of Open Access Journals (Sweden)

Óscar Fernando Motato Toro

2009-01-01

Full Text Available The evident need for improving access and safety controls has orientated the development of new personal identification systems towards using biometric, physiological and behavioral features guaranteeing increasing greater levels of performance. Motivated by this trend, the development and implementation of a computational tool for recording and validating people’s identity using dorsum hand vein images is presented here. A low-cost hardware module for acquiring infrared images was thus designed; it consisted of a conventional video-camera, optical lenses, controlled infrared illumination sources and a frame grabber. The accompanying software module was concerned with visualizing and capturing images, selecting regions of interest, pattern seg-mentation in the region and extracting, describing and classifying these features. An artificial neuron network approach was im-plemented for pattern recognition, resulting in it proving the biometric indicator to be sufficiently discriminating, and a corre-lation-based approach using a 100 image database for static characterisation, determined the system’s maximum efficiency to be 95.72% at a threshold equal to 65. False acceptance rate (FAR was 8.57% and false rejection rate (FRR was 0% at this threshold.

SU-E-I-74: Image-Matching Technique of Computed Tomography Images for Personal Identification: A Preliminary Study Using Anthropomorphic Chest Phantoms

Energy Technology Data Exchange (ETDEWEB)

Matsunobu, Y; Shiotsuki, K [Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka (Japan); Morishita, J [Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, JP (Japan)

2015-06-15

Purpose: Fingerprints, dental impressions, and DNA are used to identify unidentified bodies in forensic medicine. Cranial Computed tomography (CT) images and/or dental radiographs are also used for identification. Radiological identification is important, particularly in the absence of comparative fingerprints, dental impressions, and DNA samples. The development of an automated radiological identification system for unidentified bodies is desirable. We investigated the potential usefulness of bone structure for matching chest CT images. Methods: CT images of three anthropomorphic chest phantoms were obtained on different days in various settings. One of the phantoms was assumed to be an unidentified body. The bone image and the bone image with soft tissue (BST image) were extracted from the CT images. To examine the usefulness of the bone image and/or the BST image, the similarities between the two-dimensional (2D) or threedimensional (3D) images of the same and different phantoms were evaluated in terms of the normalized cross-correlation value (NCC). Results: For the 2D and 3D BST images, the NCCs obtained from the same phantom assumed to be an unidentified body (2D, 0.99; 3D, 0.93) were higher than those for the different phantoms (2D, 0.95 and 0.91; 3D, 0.89 and 0.80). The NCCs for the same phantom (2D, 0.95; 3D, 0.88) were greater compared to those of the different phantoms (2D, 0.61 and 0.25; 3D, 0.23 and 0.10) for the bone image. The difference in the NCCs between the same and different phantoms tended to be larger for the bone images than for the BST images. These findings suggest that the image-matching technique is more useful when utilizing the bone image than when utilizing the BST image to identify different people. Conclusion: This preliminary study indicated that evaluating the similarity of bone structure in 2D and 3D images is potentially useful for identifying of an unidentified body.

SU-E-I-74: Image-Matching Technique of Computed Tomography Images for Personal Identification: A Preliminary Study Using Anthropomorphic Chest Phantoms

International Nuclear Information System (INIS)

Matsunobu, Y; Shiotsuki, K; Morishita, J

2015-01-01

Purpose: Fingerprints, dental impressions, and DNA are used to identify unidentified bodies in forensic medicine. Cranial Computed tomography (CT) images and/or dental radiographs are also used for identification. Radiological identification is important, particularly in the absence of comparative fingerprints, dental impressions, and DNA samples. The development of an automated radiological identification system for unidentified bodies is desirable. We investigated the potential usefulness of bone structure for matching chest CT images. Methods: CT images of three anthropomorphic chest phantoms were obtained on different days in various settings. One of the phantoms was assumed to be an unidentified body. The bone image and the bone image with soft tissue (BST image) were extracted from the CT images. To examine the usefulness of the bone image and/or the BST image, the similarities between the two-dimensional (2D) or threedimensional (3D) images of the same and different phantoms were evaluated in terms of the normalized cross-correlation value (NCC). Results: For the 2D and 3D BST images, the NCCs obtained from the same phantom assumed to be an unidentified body (2D, 0.99; 3D, 0.93) were higher than those for the different phantoms (2D, 0.95 and 0.91; 3D, 0.89 and 0.80). The NCCs for the same phantom (2D, 0.95; 3D, 0.88) were greater compared to those of the different phantoms (2D, 0.61 and 0.25; 3D, 0.23 and 0.10) for the bone image. The difference in the NCCs between the same and different phantoms tended to be larger for the bone images than for the BST images. These findings suggest that the image-matching technique is more useful when utilizing the bone image than when utilizing the BST image to identify different people. Conclusion: This preliminary study indicated that evaluating the similarity of bone structure in 2D and 3D images is potentially useful for identifying of an unidentified body

Direct identification of fungi using image analysis

DEFF Research Database (Denmark)

Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

1999-01-01

Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because of the sub......Filamentous fungi have often been characterized, classified or identified with a major emphasis on macromorphological characters, i.e. the size, texture and color of fungal colonies grown on one or more identification media. This approach has been rejcted by several taxonomists because...... of the subjectivity in the visual evaluation and quantification (if any)of such characters and the apparent large variability of the features. We present an image analysis approach for objective identification and classification of fungi. The approach is exemplified by several isolates of nine different species...... of the genus Penicillium, known to be very difficult to identify correctly. The fungi were incubated on YES and CYA for one week at 25 C (3 point inoculation) in 9 cm Petri dishes. The cultures are placed under a camera where a digital image of the front of the colonies is acquired under optimal illumination...

A network identity authentication system based on Fingerprint identification technology

Science.gov (United States)

Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

2005-10-01

Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

Identification of Shielding Material Configurations Using NMIS Imaging

International Nuclear Information System (INIS)

Grogan, Brandon R.; Mihalczo, John T.; McConchie, Seth M.; Mullens, James Allen

2011-01-01

The Nuclear Materials Identification System (NMIS) uses fast neutron tomographic imaging to nonintrusively examine the interior structure of shielded objects. The pixel values in such images represent the attenuation coefficients of the time- and directionally-tagged fast neutrons from a deuterium-tritium (D T) neutron generator. The reconstruction techniques use either a filtered back projection or a maximum likelihood expectation maximization algorithm. As a first test of the capabilities of these reconstruction techniques to correctly identify individual parts inside of an object, fast neutron imaging was used to identify the regions of shielding surrounding a depleted uranium casting from a library of possible parts. The shielding consisted of multiple regions of common materials such as steel, lead, aluminum, and polyethylene. First, the full object was imaged, and then each of the individual parts was imaged. Several additional parts that were not present in the original object were also imaged to form a library. The individual parts were compared to the full object, and the correct ones were identified using three different methods. These methods included a visual match, an iterative fit of each part, and a mathematical test comparing the sum of squared errors. The successful results demonstrate an initial application of matching. This suggests that it should be possible to implement more sophisticated matching techniques using automated pixel-by-pixel comparison methods in the future.

Identification of natural images and computer-generated graphics based on statistical and textural features.

Science.gov (United States)

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Direct identification of pure penicillium species using image analysis

DEFF Research Database (Denmark)

Dørge, Thorsten Carlheim; Carstensen, Jens Michael; Frisvad, Jens Christian

2000-01-01

This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been establish...

A Study of Identification Performance of Facial Regions from CCTV Images

NARCIS (Netherlands)

Ali, Tauseef; Tome, Pedro; Fierrez, Julian; Vera-Rodriguez, Ruben; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Garain, Utpal; Shafait, Faisal

This paper focuses on automatic face identification for forensic applications. Forensic examiners compare different parts of the face image obtained from a closed-circuit television (CCTV) image with a database of mug shots or good quality image(s) taken from the suspect. In this work we study and

A study of identification performance of facial regions from CCTV images

NARCIS (Netherlands)

Ali, Tauseef; Tom, P.; Fierrez, J.; Vera-Rodriguez, R.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2012-01-01

This paper focuses on automatic face identification for forensic applications. Forensic examiners compare different parts of the face image obtained from a closed-circuit television (CCTV) image with a database of mug shots or good quality image(s) taken from the suspect. In this work we study and

Automated Photoreceptor Cell Identification on Nonconfocal Adaptive Optics Images Using Multiscale Circular Voting.

Science.gov (United States)

Liu, Jianfei; Jung, HaeWon; Dubra, Alfredo; Tam, Johnny

2017-09-01

Adaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images. Algorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data. There was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test). MSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics.

Image change detection systems, methods, and articles of manufacture

Science.gov (United States)

Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

2010-01-05

Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

Script Identification from Printed Indian Document Images and Performance Evaluation Using Different Classifiers

OpenAIRE

Sk Md Obaidullah; Anamika Mondal; Nibaran Das; Kaushik Roy

2014-01-01

Identification of script from document images is an active area of research under document image processing for a multilingual/ multiscript country like India. In this paper the real life problem of printed script identification from official Indian document images is considered and performances of different well-known classifiers are evaluated. Two important evaluating parameters, namely, AAR (average accuracy rate) and MBT (model building time), are computed for this performance analysi...

Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

Science.gov (United States)

Jani, Shyam S; Low, Daniel A; Lamb, James M

2015-01-01

To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

GrinLine identification using digital imaging and Adobe Photoshop.

Science.gov (United States)

Bollinger, Susan A; Brumit, Paula C; Schrader, Bruce A; Senn, David R

2009-03-01

The purpose of this study was to outline a method by which an antemortem photograph of a victim can be critically compared with a postmortem photograph in an effort to facilitate the identification process. Ten subjects, between 27 and 55 years old provided historical pictures of themselves exhibiting a broad smile showing anterior teeth to some extent (a grin). These photos were termed "antemortem" for the purpose of the study. A digital camera was used to take a current photo of each subject's grin. These photos represented the "postmortem" images. A single subject's "postmortem" photo set was randomly selected to be the "unknown victim." These combined data of the unknown and the 10 antemortem subjects were digitally stored and, using Adobe Photoshop software, the images were sized and oriented for comparative analysis. The goal was to devise a technique that could facilitate the accurate determination of which "antemortem" subject was the "unknown." The generation of antemortem digital overlays of the teeth visible in a grin and the comparison of those overlays to the images of the postmortem dentition is the foundation of the technique. The comparisons made using the GrinLine Identification Technique may assist medical examiners and coroners in making identifications or exclusions.

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

Science.gov (United States)

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Species identification by conservation practitioners using online images: accuracy and agreement between experts

Directory of Open Access Journals (Sweden)

Gail E. Austen

2018-01-01

Full Text Available Emerging technologies have led to an increase in species observations being recorded via digital images. Such visual records are easily shared, and are often uploaded to online communities when help is required to identify or validate species. Although this is common practice, little is known about the accuracy of species identification from such images. Using online images of newts that are native and non-native to the UK, this study asked holders of great crested newt (Triturus cristatus licences (issued by UK authorities to permit surveying for this species to sort these images into groups, and to assign species names to those groups. All of these experts identified the native species, but agreement among these participants was low, with some being cautious in committing to definitive identifications. Individuals’ accuracy was also independent of both their experience and self-assessed ability. Furthermore, mean accuracy was not uniform across species (69–96%. These findings demonstrate the difficulty of accurate identification of newts from a single image, and that expert judgements are variable, even within the same knowledgeable community. We suggest that identification decisions should be made on multiple images and verified by more than one expert, which could improve the reliability of species data.

A hyperspectral X-ray computed tomography system for enhanced material identification

Science.gov (United States)

Wu, Xiaomei; Wang, Qian; Ma, Jinlei; Zhang, Wei; Li, Po; Fang, Zheng

2017-08-01

X-ray computed tomography (CT) can distinguish different materials according to their absorption characteristics. The hyperspectral X-ray CT (HXCT) system proposed in the present work reconstructs each voxel according to its X-ray absorption spectral characteristics. In contrast to a dual-energy or multi-energy CT system, HXCT employs cadmium telluride (CdTe) as the x-ray detector, which provides higher spectral resolution and separate spectral lines according to the material's photon-counter working principle. In this paper, a specimen containing ten different polymer materials randomly arranged was adopted for material identification by HXCT. The filtered back-projection algorithm was applied for image and spectral reconstruction. The first step was to sort the individual material components of the specimen according to their cross-sectional image intensity. The second step was to classify materials with similar intensities according to their reconstructed spectral characteristics. The results demonstrated the feasibility of the proposed material identification process and indicated that the proposed HXCT system has good prospects for a wide range of biomedical and industrial nondestructive testing applications.

Parallel scan hyperspectral fluorescence imaging system and biomedical application for microarrays

International Nuclear Information System (INIS)

Liu Zhiyi; Ma Suihua; Liu Le; Guo Jihua; He Yonghong; Ji Yanhong

2011-01-01

Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.

Gaseous effluent monitoring and identification using an imaging Fourier transform spectrometer

Energy Technology Data Exchange (ETDEWEB)

Carter, M.R.; Bennett, C.L.; Fields, D.J.; Hernandez, J.

1993-10-01

We are developing an imaging Fourier transform spectrometer for chemical effluent monitoring. The system consists of a 2-D infrared imaging array in the focal plane of a Michelson interferometer. Individual images are coordinated with the positioning of a moving mirror in the Michelson interferometer. A three dimensional data cube with two spatial dimensions and one interferogram dimension is then Fourier transformed to produce a hyperspectral data cube with one spectral dimension and two spatial dimensions. The spectral range of the instrument is determined by the choice of optical components and the spectral range of the focal plane array. Measurements in the near UV, visible, near IR, and mid-IR ranges are possible with the existing instrument. Gaseous effluent monitoring and identification measurements will be primarily in the ``fingerprint`` region of the spectrum, ({lambda} = 8 to 12 {mu}m). Initial measurements of effluent using this imaging interferometer in the mid-IR will be presented.

Low-Speed Fingerprint Image Capture System User`s Guide, June 1, 1993

Energy Technology Data Exchange (ETDEWEB)

Whitus, B.R.; Goddard, J.S.; Jatko, W.B.; Manges, W.W.; Treece, D.A.

1993-06-01

The Low-Speed Fingerprint Image Capture System (LS-FICS) uses a Sun workstation controlling a Lenzar ElectroOptics Opacity 1000 imaging system to digitize fingerprint card images to support the Federal Bureau of Investigation`s (FBI`s) Automated Fingerprint Identification System (AFIS) program. The system also supports the operations performed by the Oak Ridge National Laboratory- (ORNL-) developed Image Transmission Network (ITN) prototype card scanning system. The input to the system is a single FBI fingerprint card of the agreed-upon standard format and a user-specified identification number. The output is a file formatted to be compatible with the National Institute of Standards and Technology (NIST) draft standard for fingerprint data exchange dated June 10, 1992. These NIST compatible files contain the required print and text images. The LS-FICS is designed to provide the FBI with the capability of scanning fingerprint cards into a digital format. The FBI will replicate the system to generate a data base of test images. The Host Workstation contains the image data paths and the compression algorithm. A local area network interface, disk storage, and tape drive are used for the image storage and retrieval, and the Lenzar Opacity 1000 scanner is used to acquire the image. The scanner is capable of resolving 500 pixels/in. in both x and y directions. The print images are maintained in full 8-bit gray scale and compressed with an FBI-approved wavelet-based compression algorithm. The text fields are downsampled to 250 pixels/in. and 2-bit gray scale. The text images are then compressed using a lossless Huffman coding scheme. The text fields retrieved from the output files are easily interpreted when displayed on the screen. Detailed procedures are provided for system calibration and operation. Software tools are provided to verify proper system operation.

The Development of a Parameterized Scatter Removal Algorithm for Nuclear Materials Identification System Imaging

Energy Technology Data Exchange (ETDEWEB)

Grogan, Brandon Robert [Univ. of Tennessee, Knoxville, TN (United States)

2010-03-01

This dissertation presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects non-intrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross-sections of features inside the object can be determined. The cross sections can then be used to identify the materials and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons which are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using

THE DEVELOPMENT OF A PARAMETERIZED SCATTER REMOVAL ALGORITHM FOR NUCLEAR MATERIALS IDENTIFICATION SYSTEM IMAGING

Energy Technology Data Exchange (ETDEWEB)

Grogan, Brandon R [ORNL

2010-05-01

This report presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects nonintrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross sections of features inside the object can be determined. The cross sections can then be used to identify the materials, and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons that are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized, and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements, and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using the

Statistical problems with weather-radar images, I: Clutter identification

International Nuclear Information System (INIS)

Fernandez-Duran, Juan-Jose; Upton, Graham

2003-01-01

A Markov Chain Monte Carlo (MCMC) procedure is presented for the identification of clutter in weather-radar images. The key attributes of the image are the spatial coherence of the areas of clutter (noise) and cloud and the high spatial autocorrelation of the values in areas of cloud. A form of simulated annealing provides the possibility of fast clutter removal

Autonomous identification of matrices in the APNea system

International Nuclear Information System (INIS)

Hensley, D.

1995-01-01

The APNea System is a passive and active neutron assay device which features imaging to correct for nonuniform distributions of source material. Since the imaging procedure requires a detailed knowledge of both the detection efficiency and the thermal neutron flux for (sub)volumes of the drum of interest, it is necessary to identify which mocked-up matrix, to be used for detailed characterization studies, best matches the matrix of interest. A methodology referred to as the external matrix probe (EMP) has been established which links external measures of a drum matrix to those of mocked-up matrices. These measures by themselves are sufficient to identify the appropriate mock matrix, from which the necessary characterization data are obtained. This independent matrix identification leads to an autonomous determination of the required system response parameters for the assay analysis

DIC imaging for identification of motor and sensory nerves

Directory of Open Access Journals (Sweden)

Dayu Chen

2016-09-01

Full Text Available Identification of motor and sensory nerves is important in applications such as nerve injury repair. Conventional practice relies on time consuming staining methods for this purpose. Here, we use laser scanning infrared differential interference contrast (IR-DIC microscopy for label-free observation of the two types of nerve. Ventral and dorsal nerve roots of adult beagle dogs were collected and sections of different thicknesses were imaged with an IR-DIC microscope. Different texture patterns of the IR-DIC images of the motor and sensory nerve can be distinguished when the section thickness increases to 40μm. This suggests that nerve fibers in motor and sensory nerves have different distribution patterns. The result hints a potential new way for more rapid identification of nerve type in peripheral nerve repair surgery.

[Research on Spectral Polarization Imaging System Based on Static Modulation].

Science.gov (United States)

Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

2015-04-01

The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

Identification of Complex Dynamical Systems with Neural Networks (2/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Identification of Complex Dynamical Systems with Neural Networks (1/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Trends and progress in system identification

CERN Document Server

Eykhoff, Pieter

1981-01-01

Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the """"classical"""" methods and time series estimation; application of least squares and related techniques for the e

Encryption and validation of multiple signals for optical identification systems

International Nuclear Information System (INIS)

Perez-Cabre, E; Millan, M S; Javidi, B

2007-01-01

Multifactor encryption-authentication technique reinforces optical security by allowing the simultaneous A N D-verification of more than one primary image. Instead of basing the identification on a unique signature or piece of information, our goal is to authenticate a given person, object, vehicle by the simultaneous recognition of several factors. Some of them are intrinsic to the person and object or vehicle under control. Other factors, act as keys of the authentication step. Such a system is proposed for situations such as the access control to restricted areas, where the demand of security is high. The multifactor identification method involves double random-phase encoding, fully phase-based encryption and a combined nonlinear joint transform correlator and a classical 4f-correlator for simultaneous recognition and authentication of multiple images. The encoded signal fulfils the general requirements of invisible content, extreme difficulty in counterfeiting and real-time automatic verification. Four reference double-phase encoded images are compared with the retrieved input images obtained in situ from the person or the vehicle whose authentication is wanted and from a database. A recognition step based on the correlation between the signatures and the stored references determines the authentication or rejection of the person and object under surveillance

Encryption and validation of multiple signals for optical identification systems

Energy Technology Data Exchange (ETDEWEB)

Perez-Cabre, E [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Millan, M S [Universitat PoliteGcnica de Catalunya, Department Optica i Optometria, Violinista Vellsola 37, 08222 Terrassa (Spain); Javidi, B [University of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, CT 06269 Storrs (United States)

2007-07-15

Multifactor encryption-authentication technique reinforces optical security by allowing the simultaneous A N D-verification of more than one primary image. Instead of basing the identification on a unique signature or piece of information, our goal is to authenticate a given person, object, vehicle by the simultaneous recognition of several factors. Some of them are intrinsic to the person and object or vehicle under control. Other factors, act as keys of the authentication step. Such a system is proposed for situations such as the access control to restricted areas, where the demand of security is high. The multifactor identification method involves double random-phase encoding, fully phase-based encryption and a combined nonlinear joint transform correlator and a classical 4f-correlator for simultaneous recognition and authentication of multiple images. The encoded signal fulfils the general requirements of invisible content, extreme difficulty in counterfeiting and real-time automatic verification. Four reference double-phase encoded images are compared with the retrieved input images obtained in situ from the person or the vehicle whose authentication is wanted and from a database. A recognition step based on the correlation between the signatures and the stored references determines the authentication or rejection of the person and object under surveillance.

Exploration of available feature detection and identification systems and their performance on radiographs

Science.gov (United States)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

A novel neural network based image reconstruction model with scale and rotation invariance for target identification and classification for Active millimetre wave imaging

Science.gov (United States)

Agarwal, Smriti; Bisht, Amit Singh; Singh, Dharmendra; Pathak, Nagendra Prasad

2014-12-01

Millimetre wave imaging (MMW) is gaining tremendous interest among researchers, which has potential applications for security check, standoff personal screening, automotive collision-avoidance, and lot more. Current state-of-art imaging techniques viz. microwave and X-ray imaging suffers from lower resolution and harmful ionizing radiation, respectively. In contrast, MMW imaging operates at lower power and is non-ionizing, hence, medically safe. Despite these favourable attributes, MMW imaging encounters various challenges as; still it is very less explored area and lacks suitable imaging methodology for extracting complete target information. Keeping in view of these challenges, a MMW active imaging radar system at 60 GHz was designed for standoff imaging application. A C-scan (horizontal and vertical scanning) methodology was developed that provides cross-range resolution of 8.59 mm. The paper further details a suitable target identification and classification methodology. For identification of regular shape targets: mean-standard deviation based segmentation technique was formulated and further validated using a different target shape. For classification: probability density function based target material discrimination methodology was proposed and further validated on different dataset. Lastly, a novel artificial neural network based scale and rotation invariant, image reconstruction methodology has been proposed to counter the distortions in the image caused due to noise, rotation or scale variations. The designed neural network once trained with sample images, automatically takes care of these deformations and successfully reconstructs the corrected image for the test targets. Techniques developed in this paper are tested and validated using four different regular shapes viz. rectangle, square, triangle and circle.

Mastering system identification in 100 exercises

CERN Document Server

Schoukens, J; Rolain, Yves

2012-01-01

"This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource"--

Analysis of identification of digital images from a map of cosmic microwaves

Science.gov (United States)

Skeivalas, J.; Turla, V.; Jurevicius, M.; Viselga, G.

2018-04-01

This paper discusses identification of digital images from the cosmic microwave background radiation map formed according to the data of the European Space Agency "Planck" telescope by applying covariance functions and wavelet theory. The estimates of covariance functions of two digital images or single images are calculated according to the random functions formed of the digital images in the form of pixel vectors. The estimates of pixel vectors are formed on expansion of the pixel arrays of the digital images by a single vector. When the scale of a digital image is varied, the frequencies of single-pixel color waves remain constant and the procedure for calculation of covariance functions is not affected. For identification of the images, the RGB format spectrum has been applied. The impact of RGB spectrum components and the color tensor on the estimates of covariance functions was analyzed. The identity of digital images is assessed according to the changes in the values of the correlation coefficients in a certain range of values by applying the developed computer program.

Automated Patient Identification and Localization Error Detection Using 2-Dimensional to 3-Dimensional Registration of Kilovoltage X-Ray Setup Images

International Nuclear Information System (INIS)

Lamb, James M.; Agazaryan, Nzhde; Low, Daniel A.

2013-01-01

Purpose: To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials: Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results: A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions: An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments

Automated Patient Identification and Localization Error Detection Using 2-Dimensional to 3-Dimensional Registration of Kilovoltage X-Ray Setup Images

Energy Technology Data Exchange (ETDEWEB)

Lamb, James M., E-mail: jlamb@mednet.ucla.edu; Agazaryan, Nzhde; Low, Daniel A.

2013-10-01

Purpose: To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials: Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results: A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions: An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments.

Automated patient identification and localization error detection using 2-dimensional to 3-dimensional registration of kilovoltage x-ray setup images.

Science.gov (United States)

Lamb, James M; Agazaryan, Nzhde; Low, Daniel A

2013-10-01

To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments. Copyright © 2013 Elsevier Inc. All rights reserved.

Imaging system for creating 3D block-face cryo-images of whole mice

Science.gov (United States)

Roy, Debashish; Breen, Michael; Salvado, Olivier; Heinzel, Meredith; McKinley, Eliot; Wilson, David

2006-03-01

We developed a cryomicrotome/imaging system that provides high resolution, high sensitivity block-face images of whole mice or excised organs, and applied it to a variety of biological applications. With this cryo-imaging system, we sectioned cryo-preserved tissues at 2-40 μm thickness and acquired high resolution brightfield and fluorescence images with microscopic in-plane resolution (as good as 1.2 μm). Brightfield images of normal and pathological anatomy show exquisite detail, especially in the abdominal cavity. Multi-planar reformatting and 3D renderings allow one to interrogate 3D structures. In this report, we present brightfield images of mouse anatomy, as well as 3D renderings of organs. For BPK mice model of polycystic kidney disease, we compared brightfield cryo-images and kidney volumes to MRI. The color images provided greater contrast and resolution of cysts as compared to in vivo MRI. We note that color cryo-images are closer to what a researcher sees in dissection, making it easier for them to interpret image data. The combination of field of view, depth of field, ultra high resolution and color/fluorescence contrast enables cryo-image volumes to provide details that cannot be found through in vivo imaging or other ex vivo optical imaging approaches. We believe that this novel imaging system will have applications that include identification of mouse phenotypes, characterization of diseases like blood vessel disease, kidney disease, and cancer, assessment of drug and gene therapy delivery and efficacy and validation of other imaging modalities.

DIRC, a new type of particle identification system For BABAR

International Nuclear Information System (INIS)

Schwiening, J.

1997-12-01

The DIRC, a new type of Cherenkov imaging device, has been selected as the primary particle identification system for the BABAR detector at the asymmetric B-factory, PEP-II. It is based on total internal reflection and uses long, rectangular bars made from synthetic fused silica as Cherenkov radiators and light guides. In this paper, the principles of the DIRC ring imaging Cherenkov technique are explained and results from the prototype program are presented. The studies of the optical properties and radiation hardness of the quartz radiators are described, followed by a discussion of the detector design

Modelling of Biometric Identification System with Given Parameters Using Colored Petri Nets

Science.gov (United States)

Petrosyan, G.; Ter-Vardanyan, L.; Gaboutchian, A.

2017-05-01

Biometric identification systems use given parameters and function on the basis of Colored Petri Nets as a modelling language developed for systems in which communication, synchronization and distributed resources play an important role. Colored Petri Nets combine the strengths of Classical Petri Nets with the power of a high-level programming language. Coloured Petri Nets have both, formal intuitive and graphical presentations. Graphical CPN model consists of a set of interacting modules which include a network of places, transitions and arcs. Mathematical representation has a well-defined syntax and semantics, as well as defines system behavioural properties. One of the best known features used in biometric is the human finger print pattern. During the last decade other human features have become of interest, such as iris-based or face recognition. The objective of this paper is to introduce the fundamental concepts of Petri Nets in relation to tooth shape analysis. Biometric identification systems functioning has two phases: data enrollment phase and identification phase. During the data enrollment phase images of teeth are added to database. This record contains enrollment data as a noisy version of the biometrical data corresponding to the individual. During the identification phase an unknown individual is observed again and is compared to the enrollment data in the database and then system estimates the individual. The purpose of modeling biometric identification system by means of Petri Nets is to reveal the following aspects of the functioning model: the efficiency of the model, behavior of the model, mistakes and accidents in the model, feasibility of the model simplification or substitution of its separate components for more effective components without interfering system functioning. The results of biometric identification system modeling and evaluating are presented and discussed.

Ensemble of different approaches for a reliable person re-identification system

Directory of Open Access Journals (Sweden)

Loris Nanni

2016-07-01

Full Text Available An ensemble of approaches for reliable person re-identification is proposed in this paper. The proposed ensemble is built combining widely used person re-identification systems using different color spaces and some variants of state-of-the-art approaches that are proposed in this paper. Different descriptors are tested, and both texture and color features are extracted from the images; then the different descriptors are compared using different distance measures (e.g., the Euclidean distance, angle, and the Jeffrey distance. To improve performance, a method based on skeleton detection, extracted from the depth map, is also applied when the depth map is available. The proposed ensemble is validated on three widely used datasets (CAVIAR4REID, IAS, and VIPeR, keeping the same parameter set of each approach constant across all tests to avoid overfitting and to demonstrate that the proposed system can be considered a general-purpose person re-identification system. Our experimental results show that the proposed system offers significant improvements over baseline approaches. The source code used for the approaches tested in this paper will be available at https://www.dei.unipd.it/node/2357 and http://robotics.dei.unipd.it/reid/.

REVIEW OF METHODS FOR THE SURVEILLANCE AND ACCESS CONTROL USING THE THERMAL IMAGING SYSTEM

Directory of Open Access Journals (Sweden)

Mate Krišto

2016-12-01

Full Text Available This paper presents methods for human detection for application in the field of national security in the context of state border surveillance. Except in the context of state border security, the presented methods can be applied to monitor other protected object and infrastructure such as ports and airports, power plants, water supply systems, oil pipelines, etc. Presented methods are based on use of thermal imaging systems for the human detection, recognition and identification. In addition to methods for the detection of persons, are presented and methods for face recognition and identification of the person. The use of such systems has special significance in the context of national security in the domain of timely detection of illegal crossing of state border or illegal movement near buildings, which are of special importance for national security such as traffic infrastructure facilities, power plants, military bases, especially in mountain or forests areas. In this context, thermal imaging has significant advantages over the optical camera surveillance systems because thermal imaging is robust to weather conditions and due to such an infrared thermal system can successfully applied in any weather conditions, or the periods of the day. Featured are procedures that has human detection results as well as a brief survey of specific implementation in terms of the use of infrared thermal imagers mounted on autonomous vehicles (AV and unmanned aerial vehicles (UAV. In addition to the above in this paper are described techniques and methods of face detection and human identification based on thermal image (thermogram.

Edge detection of iris of the eye for human biometric identification system

Directory of Open Access Journals (Sweden)

Kateryna O. Tryfonova

2015-03-01

Full Text Available Method of human biometric identification by iris of the eye is considered as one of the most accurate and reliable methods of identification. Aim of the research is to solve the problem of edge detection of digital image of the human eye iris to be able to implement human biometric identification system by means of mobile device. To achieve this aim the algorithm of edge detection by Canny is considered in work. It consists of the following steps: smoothing, finding gradients, non-maximum suppression, double thresholding with hysteresis. The software implementation of the Canny algorithm is carried out for the Android mobile platform with the use of high level programming language Java.

System parameter identification information criteria and algorithms

CERN Document Server

Chen, Badong; Hu, Jinchun; Principe, Jose C

2013-01-01

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors' research pr

Evaluation of the MIT RMID 1000 system for the identification of Listeria species.

Science.gov (United States)

Ricardi, John; Haavig, David; Cruz, Lasaunta; Paoli, George; Gehring, Andrew

2010-01-01

The Micro Imaging Technology (MIT) 1000 Rapid Microbial Identification (RMID) System is a device that uses the principles of light scattering coupled with proprietary algorithms to identify bacteria after being cultured and placed in a vial of filtered water. This specific method is for pure culture identification of Listeria spp. A total of 81 microorganisms (55 isolates) were tested by the MIT 1000 System, of which 25 were Listeria spp. and 30 a variety of other bacterial species. In addition, a total of 406 tests over seven different ruggedness parameters were tested by the MIT 1000 System to determine its flexibility to the specifications stated in the MIT 1000 System User Guide in areas where they might be deviated by a user to shorten the test cycle. Overall, MIT concluded that the MIT 1000 System had an accuracy performance that should certify this Performance Test Method for the identification of Listeria spp. This report discusses the tests performed, results achieved, and conclusions, along with several reference documents to enable a higher understanding of the technology used by the MIT 1000 System.

Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

Science.gov (United States)

Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

2017-02-01

We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

Construed external image and organizational identification: a test of the moderating influence of need for self-esteem.

Science.gov (United States)

Fuller, J Bryan; Marler, Laura; Hester, Kim; Frey, Len; Relyea, Clint

2006-12-01

According to Social Identity Theory (cf., J. G. March & H. A. Simon, 1958), individuals tend to identify with prestigious or high-status groups. Researchers (J. E. Dutton, J. M. Dukerich, & C. V. Harquail, 1994) have revealed that organizational members also identify with organizations that have attractive public images. To gain a better understanding of the theoretical reasons underlying the relationship between image and identification in organizations, the authors examined this relationship in a healthcare setting. In addition, they investigated need for esteem as a moderator of the relationship between construed external image and organizational identification. Consistent with previous findings, the present results indicated that construed external image is positively related to organizational identification. Perhaps it is more important that the present findings also supported need for esteem as a moderator of the relationship between construed external image and organizational identification.

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

Science.gov (United States)

Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

2013-08-01

With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

Magnetic resonance imaging identification of muscular and ligamentous structures of the female pelvic floor

International Nuclear Information System (INIS)

Bezerra, Maria Rita Lima; Soares, Adriano Fleury F.; Faintuch, Salomao; Goldman, Suzan Menasce; Ajzen, Sergio A.; D'Ippolito, Giuseppe; Szejnfeld, Jacob; Girao, Manoel

2001-01-01

The objective was to determine the frequency and to assess the interobserver agreement of identification of muscular and ligamentous pelvic floor structures using magnetic resonance imaging. The method: twenty asymptomatic female volunteers (aged 20-80 years old; mean: 50) were submitted to magnetic resonance imaging (1.5 T) examinations of the pelvis. Turbo spin-echo sequences were employed to obtain T1 and T2 weighted images on axial and sagittal planes. Two independent observers evaluated the scans in order to identify the levator ani (coccygeal, pubococcygeal, iliococcygeal and puborectalis muscles), obturatorius internus and urethral sphincter muscles, and the pubovesical and pubourethral ligaments. The frequency and the interobserver agreement of the identification of the anatomical structures were assessed (kappa statistic - κ). The results: the frequency of identification of the structures ranged from 50 to 100%, and was slightly lower for identification of the ligaments. Interobserver agreement was as follows: levator ani and obturatorius internus muscle (κ=1), pubococcygeal (κ=0.62), iliococcygeal (κ=0.86), puborectalis (κ= 0.27), coccygeal (κ=0) and urethral sphincter muscles (κ=1), pubovesical (κ=0.50) and pubourethral (κ=0.58) ligaments. The conclusion: magnetic resonance imaging of the pelvis allowed precise identification of the main muscular and ligamentous pelvic floor structures in most individuals, whereas interobserver agreement was considered good. (author)

Use of images for human identification in forensic dentistry

International Nuclear Information System (INIS)

Carvalho, Suzana Papile Maciel; Lopes-Junior, Cesar; Silva, Ricardo Henrique Alves da; Peres, Arsenio Sales

2009-01-01

The present systematic review article is aimed at describing radiological methods utilized for human identification in forensic dentistry. For this purpose, a literature review was undertaken, and out of 45 papers, 19 were selected in accordance with inclusion criteria. Several radiological techniques can be used to assist in both individual and general identification, including determination of gender, ethnic group and, mainly, age. The analysis of ante-mortem and post-mortem radiographic and tomographic images has become an essential tool for human identification in forensic dentistry, particularly with the refinement of techniques resulting from developments in the field of the radiology itself as well as the incorporation of information technology resources to the technique. It can be concluded that, based on an appropriate knowledge on the available methods, forensic dentists can choose the best method to achieve a successful identification with a careful application of the technique and accurate interpretation of data. (author)

Time-Delay System Identification Using Genetic Algorithm

DEFF Research Database (Denmark)

Yang, Zhenyu; Seested, Glen Thane

2013-01-01

Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique. The qual......Due to the unknown dead-time coefficient, the time-delay system identification turns to be a non-convex optimization problem. This paper investigates the identification of a simple time-delay system, named First-Order-Plus-Dead-Time (FOPDT), by using the Genetic Algorithm (GA) technique...

Craniofacial Manifestations of Systemic Disorders: CT and MR Imaging Findings and Imaging Approach.

Science.gov (United States)

Andreu-Arasa, V Carlota; Chapman, Margaret N; Kuno, Hirofumi; Fujita, Akifumi; Sakai, Osamu

2018-01-01

Many systemic diseases or conditions can affect the maxillofacial bones; however, they are often overlooked or incidentally found at routine brain or head and neck imaging performed for other reasons. Early identification of some conditions may significantly affect patient care and alter outcomes. Early recognition of nonneoplastic hematologic disorders, such as thalassemia and sickle cell disease, may help initiate earlier treatment and prevent serious complications. The management of neoplastic diseases such as lymphoma, leukemia, or Langerhans cell histiocytosis may be different if diagnosed early, and metastases to the maxillofacial bones may be the first manifestation of an otherwise occult neoplasm. Endocrinologic and metabolic disorders also may manifest with maxillofacial conditions. Earlier recognition of osteoporosis may alter treatment and prevent complications such as insufficiency fractures, and identification of acromegaly may lead to surgical treatment if there is an underlying growth hormone-producing adenoma. Bone dysplasias sometimes are associated with skull base foraminal narrowing and subsequent involvement of the cranial nerves. Inflammatory processes such as rheumatoid arthritis and sarcoidosis may affect the maxillofacial bones, skull base, and temporomandibular joints. Radiologists should be familiar with the maxillofacial computed tomographic and magnetic resonance imaging findings of common systemic disorders because these may be the first manifestations of an otherwise unrevealed systemic process with potential for serious complications. Online supplemental material is available for this article. © RSNA, 2018.

Electro-optical fuel pin identification system

International Nuclear Information System (INIS)

Kirchner, T.L.

1978-09-01

A prototype Electro-Optical Fuel Pin Identification System referred to as the Fuel Pin Identification System (FPIS) has been developed by the Hanford Engineering Development Laboratory (HEDL) in support of the Fast Flux Test Facility (FFTF) presently under construction at HEDL. The system is designed to remotely read an alpha-numeric identification number that is roll stamped on the top of the fuel pin end cap. The prototype FPIS consists of four major subassemblies: optical read head, digital compression electronics, video display, and line printer

On System Identification of Wind Turbines

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Perisic, Nevena; Pedersen, B.J.

Recently several methods have been proposed for the system identification of wind turbines which can be considered as a linear time-varying system due to the operating conditions. For the identification of linear wind turbine models, either black-box or grey-box identification can be used....... The operational model analysis (OMA) methodology can provide accurate estimates of the natural frequencies, damping ratios and mode shapes of the systems as long as the measurements have a low noise to signal ratio. However, in order to take information about the wind turbine into account a grey...

System Identification with Quantized Observations

CERN Document Server

Wang, Le Yi; Zhang, Jifeng; Zhao, Yanlong

2010-01-01

This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed. Providing a comprehensive coverage of quantized identification,

Modular spectral imaging system for discrimination of pigments in cells and microbial communities.

Science.gov (United States)

Polerecky, Lubos; Bissett, Andrew; Al-Najjar, Mohammad; Faerber, Paul; Osmers, Harald; Suci, Peter A; Stoodley, Paul; de Beer, Dirk

2009-02-01

Here we describe a spectral imaging system for minimally invasive identification, localization, and relative quantification of pigments in cells and microbial communities. The modularity of the system allows pigment detection on spatial scales ranging from the single-cell level to regions whose areas are several tens of square centimeters. For pigment identification in vivo absorption and/or autofluorescence spectra are used as the analytical signals. Along with the hardware, which is easy to transport and simple to assemble and allows rapid measurement, we describe newly developed software that allows highly sensitive and pigment-specific analyses of the hyperspectral data. We also propose and describe a number of applications of the system for microbial ecology, including identification of pigments in living cells and high-spatial-resolution imaging of pigments and the associated phototrophic groups in complex microbial communities, such as photosynthetic endolithic biofilms, microbial mats, and intertidal sediments. This system provides new possibilities for studying the role of spatial organization of microorganisms in the ecological functioning of complex benthic microbial communities or for noninvasively monitoring changes in the spatial organization and/or composition of a microbial community in response to changing environmental factors.

Embedded System for Biometric Identification

OpenAIRE

Rosli, Ahmad Nasir Che

2010-01-01

This chapter describes the design and implementation of an Embedded System for Biometric Identification from hardware and software perspectives. The first part of the chapter describes the idea of biometric identification. This includes the definition of

Review of fluorescence guided surgery systems: identification of key performance capabilities beyond indocyanine green imaging

Science.gov (United States)

DSouza, Alisha V.; Lin, Huiyun; Henderson, Eric R.; Samkoe, Kimberley S.; Pogue, Brian W.

2016-01-01

Abstract. There is growing interest in using fluorescence imaging instruments to guide surgery, and the leading options for open-field imaging are reviewed here. While the clinical fluorescence-guided surgery (FGS) field has been focused predominantly on indocyanine green (ICG) imaging, there is accelerated development of more specific molecular tracers. These agents should help advance new indications for which FGS presents a paradigm shift in how molecular information is provided for resection decisions. There has been a steady growth in commercially marketed FGS systems, each with their own differentiated performance characteristics and specifications. A set of desirable criteria is presented to guide the evaluation of instruments, including: (i) real-time overlay of white-light and fluorescence images, (ii) operation within ambient room lighting, (iii) nanomolar-level sensitivity, (iv) quantitative capabilities, (v) simultaneous multiple fluorophore imaging, and (vi) ergonomic utility for open surgery. In this review, United States Food and Drug Administration 510(k) cleared commercial systems and some leading premarket FGS research systems were evaluated to illustrate the continual increase in this performance feature base. Generally, the systems designed for ICG-only imaging have sufficient sensitivity to ICG, but a fraction of the other desired features listed above, with both lower sensitivity and dynamic range. In comparison, the emerging research systems targeted for use with molecular agents have unique capabilities that will be essential for successful clinical imaging studies with low-concentration agents or where superior rejection of ambient light is needed. There is no perfect imaging system, but the feature differences among them are important differentiators in their utility, as outlined in the data and tables here. PMID:27533438

Review of fluorescence guided surgery systems: identification of key performance capabilities beyond indocyanine green imaging

Science.gov (United States)

DSouza, Alisha V.; Lin, Huiyun; Henderson, Eric R.; Samkoe, Kimberley S.; Pogue, Brian W.

2016-08-01

There is growing interest in using fluorescence imaging instruments to guide surgery, and the leading options for open-field imaging are reviewed here. While the clinical fluorescence-guided surgery (FGS) field has been focused predominantly on indocyanine green (ICG) imaging, there is accelerated development of more specific molecular tracers. These agents should help advance new indications for which FGS presents a paradigm shift in how molecular information is provided for resection decisions. There has been a steady growth in commercially marketed FGS systems, each with their own differentiated performance characteristics and specifications. A set of desirable criteria is presented to guide the evaluation of instruments, including: (i) real-time overlay of white-light and fluorescence images, (ii) operation within ambient room lighting, (iii) nanomolar-level sensitivity, (iv) quantitative capabilities, (v) simultaneous multiple fluorophore imaging, and (vi) ergonomic utility for open surgery. In this review, United States Food and Drug Administration 510(k) cleared commercial systems and some leading premarket FGS research systems were evaluated to illustrate the continual increase in this performance feature base. Generally, the systems designed for ICG-only imaging have sufficient sensitivity to ICG, but a fraction of the other desired features listed above, with both lower sensitivity and dynamic range. In comparison, the emerging research systems targeted for use with molecular agents have unique capabilities that will be essential for successful clinical imaging studies with low-concentration agents or where superior rejection of ambient light is needed. There is no perfect imaging system, but the feature differences among them are important differentiators in their utility, as outlined in the data and tables here.

Hyperspectral imager for components identification in the atmosphere

Science.gov (United States)

Dewandel, Jean-Luc; Beghuin, Didier; Dubois, Xavier; Antoine, Philippe

2017-11-01

Several applications require the identification of chemical elements during re-entry of material in the atmosphere. The materials can be from human origin or meteorites. The Automated Transfer Vehicle (ATV) re-entry has been filmed with conventional camera from airborne manual operation. In order to permit the identification of the separate elements from their glow, spectral analysis needs to be added to the video data. In a LET-SME contract with ESA, Lambda-X has built a Fourier Transform Imaging Spectrometer to permit, in a future work, to bring the technology to the readiness level required for the application. In this paper, the principles of the Fourier Transform Imaging spectroscopy are recalled, the different interferometers suitable for supporting the technique are reviewed and the selection process is explained. The final selection of the interferometer corresponds to a birefringent prism based common path shear interferometer. The design of the breadboard and its performances are presented in terms of spatial resolution, aperture, and spectral resolution. A discussion is open regarding perspective of the technique for other remote sensing applications compared to more usual push broom configurations.

Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

Science.gov (United States)

Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

2012-01-01

The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification

Directory of Open Access Journals (Sweden)

Ayedh Alqahtani

2016-01-01

Full Text Available Solar photovoltaic (PV energy sources are rapidly gaining potential growth and popularity compared to conventional fossil fuel sources. As the merging of PV systems with existing power sources increases, reliable and accurate PV system identification is essential, to address the highly nonlinear change in PV system dynamic and operational characteristics. This paper deals with the identification of a PV system characteristic with a switch-mode power converter. Measured input-output data are collected from a real PV panel to be used for the identification. The data are divided into estimation and validation sets. The identification methodology is discussed. A Hammerstein-Wiener model is identified and selected due to its suitability to best capture the PV system dynamics, and results and discussion are provided to demonstrate the accuracy of the selected model structure.

Genetic Algorithm-Based Identification of Fractional-Order Systems

Directory of Open Access Journals (Sweden)

Shengxi Zhou

2013-05-01

Full Text Available Fractional calculus has become an increasingly popular tool for modeling the complex behaviors of physical systems from diverse domains. One of the key issues to apply fractional calculus to engineering problems is to achieve the parameter identification of fractional-order systems. A time-domain identification algorithm based on a genetic algorithm (GA is proposed in this paper. The multi-variable parameter identification is converted into a parameter optimization by applying GA to the identification of fractional-order systems. To evaluate the identification accuracy and stability, the time-domain output error considering the condition variation is designed as the fitness function for parameter optimization. The identification process is established under various noise levels and excitation levels. The effects of external excitation and the noise level on the identification accuracy are analyzed in detail. The simulation results show that the proposed method could identify the parameters of both commensurate rate and non-commensurate rate fractional-order systems from the data with noise. It is also observed that excitation signal is an important factor influencing the identification accuracy of fractional-order systems.

Development of on-chip multi-imaging flow cytometry for identification of imaging biomarkers of clustered circulating tumor cells.

Directory of Open Access Journals (Sweden)

Hyonchol Kim

Full Text Available An on-chip multi-imaging flow cytometry system has been developed to obtain morphometric parameters of cell clusters such as cell number, perimeter, total cross-sectional area, number of nuclei and size of clusters as "imaging biomarkers", with simultaneous acquisition and analysis of both bright-field (BF and fluorescent (FL images at 200 frames per second (fps; by using this system, we examined the effectiveness of using imaging biomarkers for the identification of clustered circulating tumor cells (CTCs. Sample blood of rats in which a prostate cancer cell line (MAT-LyLu had been pre-implanted was applied to a microchannel on a disposable microchip after staining the nuclei using fluorescent dye for their visualization, and the acquired images were measured and compared with those of healthy rats. In terms of the results, clustered cells having (1 cell area larger than 200 µm2 and (2 nucleus area larger than 90 µm2 were specifically observed in cancer cell-implanted blood, but were not observed in healthy rats. In addition, (3 clusters having more than 3 nuclei were specific for cancer-implanted blood and (4 a ratio between the actual perimeter and the perimeter calculated from the obtained area, which reflects a shape distorted from ideal roundness, of less than 0.90 was specific for all clusters having more than 3 nuclei and was also specific for cancer-implanted blood. The collected clusters larger than 300 µm2 were examined by quantitative gene copy number assay, and were identified as being CTCs. These results indicate the usefulness of the imaging biomarkers for characterizing clusters, and all of the four examined imaging biomarkers-cluster area, nuclei area, nuclei number, and ratio of perimeter-can identify clustered CTCs in blood with the same level of preciseness using multi-imaging cytometry.

Fusion of High b-valve diffusion-weighted and T2-weighted MR images improves identification of lymph nodes in the pelvis

International Nuclear Information System (INIS)

Mir, N.; Sohaib, S.A.; Collins, D.; Koh, D.M.

2010-01-01

Full text: Accurate identification of lymph nodes facilities nodal assessment by size, morphological or MR lymphographic criteria. We compared the MR detection of lymph nodes in patients with pelvic cancers using T2-weighted imaging, and fusion of diffusion-weighted imaging (OWl) and T2-weighted imaging. Twenty patients with pelvic tumours underwent 5-mm axial T2-weighted and OWl (b-values 0-750 s/mm 2 ) on a L 5T system. Fusion images of b = 750 s/mm 2 diffusion-weighted MR and T2-weighted images were created. Two radiologists evaluated in consensus the T2-weighted images and fusion images independently. For each image set, the location and diameter of pelvic nodes were recorded, and nodal visibility was scored using a 4-point scale (0-3). Nodal visualisation was compared using Relative to an Identified Distribution (RIDIT) analysis. The mean RIDIT score describes the probability that a randomly selected node will be better visualised relative to the other image set. One hundred fourteen pelvic nodes (mean 5.9 mm; 2-10 mm) were identified on T2-weighted images and 161 nodes (mean 4.3 mm; 2-10 mm) on fusion images. Using fusion images, 47 additional nodes were detected compared with T2-weighted images alone (eight external iliac, 24 inguinal, 12 obturator, two peri-rectal, one presacral). Nodes detected only on fusion images were 2-9 mm (mean 3.7 mm). Nodal visualisation was better using fusion images compared with T2-weighted images (mean RIDIT score 0.689 vs 0.302). Fusion of diffusion-weighted MR with T2-weighted images improves identification of pelvic lymph nodes compared with T2-weighted images alone. The improved nodal identification may aid treatment planning and further nodal characterisation.

Design and development of a prototype hot spot identification system

International Nuclear Information System (INIS)

Jain, Amit; Thakur, Vaishali M.; Anilkumar, Rekha; Sawant, Pravin; Chaudhury, Probal; Pradeepkumar, K.S.

2015-01-01

The proper assessment of radiological environments inside nuclear facilities require accurate spatial mapping of the gamma ray field. A prototype Hotspot Identification System has been designed and developed in-house for gamma ray imaging by combining a gamma spectrometer with a pinhole collimator and a digital camera. The system can rapidly determine the location, distribution and intensity of gamma ray sources by carrying a scan of the suspected locations. The measured data was compared with simulated values for NaI(Tl) response, generated using the MCNP 4B Transport code. The data obtained by experimental and theoretical method are in good agreement. (author)

Fuel number identification method and device

International Nuclear Information System (INIS)

Doi, Takami; Seno, Makoto; Kikuchi, Takashi; Sakamoto, Hiromi; Takahashi, Masaki; Tanaka, Keiji.

1997-01-01

The present invention provides a method of and a device for automatically identifying fuel numbers impressed on fuel assemblies disposed in a fuel reprocessing facility, power plant and a reactor core at a high speed and at a high identification rate. Namely, three or more character images are photographed for one fuel assembly as an object of the identification under different illumination conditions. As a result, different character images by the number of the illumination directions can be obtained for identical impressed characters. Learning on a neural network system is applied to the images of all of the characters impressed on the fuel assembly obtained under illumination of predetermined directions. Then, result of the identification by the number of the illumination directions can be obtained for each of the characters as an object of the identification. As a result, since the result of the identification is determined based on a theory of decision of majority, highly automatic identification can be realized. (I.S.)

Active thermography and post-processing image enhancement for recovering of abraded and paint-covered alphanumeric identification marks

DEFF Research Database (Denmark)

Montanini, R.; Quattrocchi, A.; Piccolo, Sebastiano

2016-01-01

Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery of the l......Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery...... by means of different manufacturing processes (laser, dot peen, impact, cold press and scribe). Optical excitation of the target surface has been achieved using pulse (PT), lock-in (LT) and step heating (SHT) thermography. Raw infrared images were analysed with a dedicated image processing software...... originally developed in Matlab™, exploiting several methods, which include thermographic signal reconstruction (TSR), guided filtering (GF), block guided filtering (BGF) and logarithmic transformation (LN). Proper image processing of the raw infrared images resulted in superior contrast and enhanced...

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.

Access control and personal identification systems

CERN Document Server

Bowers, Dan M

1988-01-01

Access Control and Personal Identification Systems provides an education in the field of access control and personal identification systems, which is essential in selecting the appropriate equipment, dealing intelligently with vendors in purchases of the equipment, and integrating the equipment into a total effective system. Access control devices and systems comprise an important part of almost every security system, but are seldom the sole source of security. In order for the goals of the total system to be met, the other portions of the security system must also be well planned and executed

Identification method of gas-liquid two-phase flow regime based on image wavelet packet information entropy and genetic neural network

International Nuclear Information System (INIS)

Zhou Yunlong; Chen Fei; Sun Bin

2008-01-01

Based on the characteristic that wavelet packet transform image can be decomposed by different scales, a flow regime identification method based on image wavelet packet information entropy feature and genetic neural network was proposed. Gas-liquid two-phase flow images were captured by digital high speed video systems in horizontal pipe. The information entropy feature from transformation coefficients were extracted using image processing techniques and multi-resolution analysis. The genetic neural network was trained using those eigenvectors, which was reduced by the principal component analysis, as flow regime samples, and the flow regime intelligent identification was realized. The test result showed that image wavelet packet information entropy feature could excellently reflect the difference between seven typical flow regimes, and the genetic neural network with genetic algorithm and BP algorithm merits were with the characteristics of fast convergence for simulation and avoidance of local minimum. The recognition possibility of the network could reach up to about 100%, and a new and effective method was presented for on-line flow regime. (authors)

Influence of detector collimation and beam pitch for identification and image quality of ground-glass attenuation and nodules on 16- and 64-detector row CT systems: experimental study using chest phantom.

Science.gov (United States)

Ohno, Yoshiharu; Koyama, Hisanobu; Kono, Astushi; Terada, Mari; Inokawa, Hiroyasu; Matsumoto, Sumiaki; Sugimura, Kazuro

2007-12-01

The purpose of the present study was to determine the influence of detector collimation and beam pitch for identification and image quality of ground-glass attenuation (GGA) and nodules on 16- and 64-detector row CTs, by using a commercially available chest phantom. A chest CT phantom including simulated GGAs and nodules was scanned with different detector collimations, beam pitches and tube currents. The probability and image quality of each simulated abnormality was visually assessed with a five-point scoring system. ROC-analysis and ANOVA were then performed to compare the identification and image quality of either protocol with standard values. Detection rates of low-dose CTs were significantly reduced when tube currents were set at 40mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32mmx1.0mm for low pitch, and at 100mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32mmx1.0mm for high pitch (pdetector collimation 16 and 64x0.5mm and 16 and 32x1.0mm for low pitch, and at 150mA or less by using detector collimation 16 and 64x0.5mm and 16 and 32x1.0mm for high pitch (pDetector collimation and beam pitch were important factors for the image quality and identification of GGA and nodules by 16- and 64-detector row CT.

The diagnostic value of adding dynamic scintigraphy to standard delayed planar imaging for sentinel node identification in melanoma patients

DEFF Research Database (Denmark)

Nielsen, Marie Kristina Rue; Chakera, Annette H; Hesse, Birger

2011-01-01

The aim of this study was to compare early dynamic imaging combined with delayed static imaging and single photon emission computed tomography (SPECT)/CT with delayed, planar, static imaging alone for sentinel node (SN) identification in melanoma patients.......The aim of this study was to compare early dynamic imaging combined with delayed static imaging and single photon emission computed tomography (SPECT)/CT with delayed, planar, static imaging alone for sentinel node (SN) identification in melanoma patients....

Automatic slice identification in 3D medical images with a ConvNet regressor

NARCIS (Netherlands)

de Vos, Bob D.; Viergever, Max A.; de Jong, Pim A.; Išgum, Ivana

2016-01-01

Identification of anatomical regions of interest is a prerequisite in many medical image analysis tasks. We propose a method that automatically identifies a slice of interest (SOI) in 3D images with a convolutional neural network (ConvNet) regressor. In 150 chest CT scans two reference slices were

Gabor filter based fingerprint image enhancement

Science.gov (United States)

Wang, Jin-Xiang

2013-03-01

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

Medical Imaging System

Science.gov (United States)

1991-01-01

The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

Cost Optimal System Identification Experiment Design

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...

Identification and Damage Detection on Structural Systems

DEFF Research Database (Denmark)

Brincker, Rune; Kirkegaard, Poul Henning; Andersen, Palle

1994-01-01

A short introduction is given to system identification and damage assessment in civil engineering structures. The most commonly used FFT-based techniques for system identification are mentioned, and the Random decrement technique and parametric methods based on ARMA models are introduced. Speed...

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

Science.gov (United States)

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving

A review of techniques for the identification and measurement of fish in underwater stereo-video image sequences

Science.gov (United States)

Shortis, Mark R.; Ravanbakskh, Mehdi; Shaifat, Faisal; Harvey, Euan S.; Mian, Ajmal; Seager, James W.; Culverhouse, Philip F.; Cline, Danelle E.; Edgington, Duane R.

2013-04-01

Underwater stereo-video measurement systems are used widely for counting and measuring fish in aquaculture, fisheries and conservation management. To determine population counts, spatial or temporal frequencies, and age or weight distributions, snout to fork length measurements are captured from the video sequences, most commonly using a point and click process by a human operator. Current research aims to automate the measurement and counting task in order to improve the efficiency of the process and expand the use of stereo-video systems within marine science. A fully automated process will require the detection and identification of candidates for measurement, followed by the snout to fork length measurement, as well as the counting and tracking of fish. This paper presents a review of the techniques used for the detection, identification, measurement, counting and tracking of fish in underwater stereo-video image sequences, including consideration of the changing body shape. The review will analyse the most commonly used approaches, leading to an evaluation of the techniques most likely to be a general solution to the complete process of detection, identification, measurement, counting and tracking.

Analysis of blind identification methods for estimation of kinetic parameters in dynamic medical imaging

Science.gov (United States)

Riabkov, Dmitri

Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well-modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. In this work it is shown that the blind identification problem has a unique solution for two-compartment model tissue response. For two-compartment model tissue responses in dynamic cardiac MRI imaging conditions with gadolinium-DTPA contrast agent, three blind identification algorithms are analyzed here to assess their utility: Eigenvector-based Algorithm for Multichannel Blind Deconvolution (EVAM), Cross Relations (CR), and Iterative Quadratic Maximum Likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that the IQML method gives more accurate estimates than the other two blind identification methods. A proof is presented here that three-compartment model blind identification is not unique in the case of only two regions. It is shown that it is likely unique for the case of more than two regions, but this has not been proved analytically. For the three-compartment model the tissue responses in dynamic FDG PET imaging conditions are analyzed with the blind identification algorithms EVAM and Separable variables Least Squares (SLS). A method of

Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

Science.gov (United States)

Suzani, Amin; Rasoulian, Abtin; Seitel, Alexander; Fels, Sidney; Rohling, Robert N.; Abolmaesumi, Purang

2015-03-01

This paper proposes an automatic method for vertebra localization, labeling, and segmentation in multi-slice Magnetic Resonance (MR) images. Prior work in this area on MR images mostly requires user interaction while our method is fully automatic. Cubic intensity-based features are extracted from image voxels. A deep learning approach is used for simultaneous localization and identification of vertebrae. The localized points are refined by local thresholding in the region of the detected vertebral column. Thereafter, a statistical multi-vertebrae model is initialized on the localized vertebrae. An iterative Expectation Maximization technique is used to register the vertebral body of the model to the image edges and obtain a segmentation of the lumbar vertebral bodies. The method is evaluated by applying to nine volumetric MR images of the spine. The results demonstrate 100% vertebra identification and a mean surface error of below 2.8 mm for 3D segmentation. Computation time is less than three minutes per high-resolution volumetric image.

Incremental Closed-loop Identification of Linear Parameter Varying Systems

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Trangbæk, Klaus

2011-01-01

, closed-loop system identification is more difficult than open-loop identification. In this paper we prove that the so-called Hansen Scheme, a technique known from linear time-invariant systems theory for transforming closed-loop system identification problems into open-loop-like problems, can be extended...

Do strict rules and moving images increase the reliability of sequential identification procedures?.

OpenAIRE

Valentine, Tim; Darling, Stephen; Memon, Amina

2007-01-01

Live identification procedures in England and Wales have been replaced by use of video, which provides a sequential presentation of facial images. Sequential presentation of photographs provides some protection to innocent suspects from mistaken identification when used with strict instructions designed to prevent relative judgements (Lindsay, Lea & Fulford, 1991). However, the current procedure in England and Wales is incompatible with these strict instructions. The reported research investi...

System for accessing a collection of histology images using content-based strategies

International Nuclear Information System (INIS)

Gonzalez F; Caicedo J C; Cruz Roa A; Camargo, J; Spinel, C

2010-01-01

Histology images are an important resource for research, education and medical practice. The availability of image collections with reference purposes is limited to printed formats such as books and specialized journals. When histology image sets are published in digital formats, they are composed of some tens of images that do not represent the wide diversity of biological structures that can be found in fundamental tissues; making a complete histology image collection available to the general public having a great impact on research and education in different areas such as medicine, biology and natural sciences. This work presents the acquisition process of a histology image collection with 20,000 samples in digital format, from tissue processing to digital image capturing. The main purpose of collecting these images is to make them available as reference material to the academic community. In addition, this paper presents the design and architecture of a system to query and explore the image collection, using content-based image retrieval tools and text-based search on the annotations provided by experts. The system also offers novel image visualization methods to allow easy identification of interesting images among hundreds of possible pictures. The system has been developed using a service-oriented architecture and allows web-based access in http://www.informed.unal.edu.co

Automated identification of intergranular corrosion in X-ray CT images

International Nuclear Information System (INIS)

Howell, Patricia A.; Winfree, William P.

2003-01-01

Characterization of a material or structure by computed tomography results in the acquisition of large quantities of data that need to be tediously examined to determine the location and size of damage. Since the computed tomography images are digital, there is significant potential for reducing the human effort evolved in this process by digital processing of this data to enhance the signatures of flaws and perform automated identification of suspected flaws. Techniques are presented that enhance the contrast between corroded and uncorroded regions to simplify the analysis and improve quality of flaw identification. Algorithms developed in part for computer vision, such as anisotropic diffusion and edge detection techniques, are applied to the data. Anisotropic diffusion techniques are shown to significantly reduce image noise while maintaining the contrast between intergranular corrosion and uncorroded regions and preserving the important features of the flaw. Edge detection techniques are shown to enable a rapid location of regions requiring further analysis. In regions identified by the edge detection technique, neural network techniques are applied to automate defect detection of the intergranular corrosion

System Identification A Frequency Domain Approach

CERN Document Server

Pintelon, Rik

2012-01-01

System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identi

A novel and compact spectral imaging system based on two curved prisms

Science.gov (United States)

Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

2013-09-01

As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

A portable neutron spectroscope (NSPECT) for detection, imaging and identification of nuclear material

Science.gov (United States)

Ryan, James M.; Bancroft, Christopher; Bloser, Peter; Bravar, Ulisse; Fourguette, Dominique; Frost, Colin; Larocque, Liane; McConnell, Mark L.; Legere, Jason; Pavlich, Jane; Ritter, Greg; Wassick, Greg; Wood, Joshua; Woolf, Richard

2010-08-01

We have developed, fabricated and tested a prototype imaging neutron spectrometer designed for real-time neutron source location and identification. Real-time detection and identification is important for locating materials. These materials, specifically uranium and transuranics, emit neutrons via spontaneous or induced fission. Unlike other forms of radiation (e.g. gamma rays), penetrating neutron emission is very uncommon. The instrument detects these neutrons, constructs images of the emission pattern, and reports the neutron spectrum. The device will be useful for security and proliferation deterrence, as well as for nuclear waste characterization and monitoring. The instrument is optimized for imaging and spectroscopy in the 1-20 MeV range. The detection principle is based upon multiple elastic neutron-proton scatters in organic scintillator. Two detector panel layers are utilized. By measuring the recoil proton and scattered neutron locations and energies, the direction and energy spectrum of the incident neutrons can be determined and discrete and extended sources identified. Event reconstruction yields an image of the source and its location. The hardware is low power, low mass, and rugged. Its modular design allows the user to combine multiple units for increased sensitivity. We will report the results of laboratory testing of the instrument, including exposure to a calibrated Cf-252 source. Instrument parameters include energy and angular resolution, gamma rejection, minimum source identification distances and times, and projected effective area for a fully populated instrument.

Decoupling Identification for Serial Two-Link Two-Inertia System

Science.gov (United States)

Oaki, Junji; Adachi, Shuichi

The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.

Closed-loop System Identification with New Sensors

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

2008-01-01

This paper deals with system identification of new system dynamics revealed by online introduction of new sensors in existing multi-variable linear control systems. The so-called "Hansen Scheme" utilises the dual Youla-Kucera parameterisation of all systems stabilised by a given linear controller...... to transform closed-loop system identification problems into open-loop-like problems. We show that this scheme can be formally extended to accomodate extra sensors in a nice way. The approach is illustrated on a simple simulation example....

Curved planar reformation images for identification of the central sulcus of affected hemispheres. Comparison with functional magnetic resonance imaging

International Nuclear Information System (INIS)

Nishimoto, Hideaki; Inoue, Takashi

2006-01-01

The aim of the present study was to evaluate the curved planar reformation (CPR) for identification of the central sulcus on affected hemispheres. Thirty four patients with an intracranial lesion adjacent to the central sulcus underwent functional magnetic resonance imaging (fMRI). fMRI was performed with a 3.0 Tesla scanner during repetitive opening and closing of each hand. The central sulcus was defined as the nearest sulcus to the highest activation spots. Three-dimensional magnetic resonance imaging date sets were processed using the CPR method to create brain surface reformatted images. We evaluated five anatomical features widely used for clinical identification of the central sulcus: 1, termination of the superior frontal sulcus in the precentral sulcus; 2, the intraparietal sulcus joining the postcentral sulcus; 3, the precentral gyros thicker than the postcentral gyrus; 4, inverted omega-shape of the precentral gyrus; and 5, the central sulcus as an isolated sulcus. fMRI and CPR coincided in defining the central sulcus in 34 hemispheres of patients. Applicability of each of the five signs was 61.8, 73.5, 58.8, 50.0 and 67.6%, respectively. The present study indicates that the CPR method successfully defined the central sulcus in most patients with brain tumors. For identification of the central sulcus, the CPR method will be recommended. (author)

75 FR 25137 - Changes to Standard Numbering System, Vessel Identification System, and Boating Accident Report...

Science.gov (United States)

2010-05-07

...-2003-14963] RIN 1625-AB45 Changes to Standard Numbering System, Vessel Identification System, and... System (SNS), the Vessel Identification System (VIS), and casualty reporting; require validation of... Standard Numbering System U.S.C. United States Code VIS Vessel Identification System III. Background Coast...

A bimodal biometric identification system

Science.gov (United States)

Laghari, Mohammad S.; Khuwaja, Gulzar A.

2013-03-01

Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

Multi-level RF identification system

Science.gov (United States)

Steele, Kerry D.; Anderson, Gordon A.; Gilbert, Ronald W.

2004-07-20

A radio frequency identification system having a radio frequency transceiver for generating a continuous wave RF interrogation signal that impinges upon an RF identification tag. An oscillation circuit in the RF identification tag modulates the interrogation signal with a subcarrier of a predetermined frequency and modulates the frequency-modulated signal back to the transmitting interrogator. The interrogator recovers and analyzes the subcarrier signal and determines its frequency. The interrogator generates an output indicative of the frequency of the subcarrier frequency, thereby identifying the responding RFID tag as one of a "class" of RFID tags configured to respond with a subcarrier signal of a predetermined frequency.

A Robust Identification of the Protein Standard Bands in Two-Dimensional Electrophoresis Gel Images

Directory of Open Access Journals (Sweden)

Serackis Artūras

2017-12-01

Full Text Available The aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the positions of the markers, prepared by using pre-selected proteins with known molecular mass. The robustness of the method was achieved by using special validation rules in the proposed original algorithms. In addition, a self-organizing map-based decision support algorithm is proposed, which takes Gabor coefficients as image features and searches for the differences in preselected vertical image bars. The experimental investigation proved the good performance of the new algorithms included into the proposed method. The detection of the protein standard markers works without modification of algorithm parameters on two-dimensional gel images obtained by using different staining and destaining procedures, which results in different average levels of intensity in the images.

Writer identification system for Ethiopic handwriting | Demoze | Zede ...

African Journals Online (AJOL)

Writer identification is a popular and ongoing research area having a wide variety of applications in banking, criminal justice system, access control, determining the authenticity of handwritten mails, etc. In this paper, an off-line text independent Ethiopic writer identification system has been proposed. The system uses 50 ...

Medical imaging systems

Science.gov (United States)

Frangioni, John V [Wayland, MA

2012-07-24

A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remains in a subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may also employ dyes or other fluorescent substances associated with antibodies, antibody fragments, or ligands that accumulate within a region of diagnostic significance. In one embodiment, the system provides an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide that is used to capture images. In another embodiment, the system is configured for use in open surgical procedures by providing an operating area that is closed to ambient light. More broadly, the systems described herein may be used in imaging applications where a visible light image may be usefully supplemented by an image formed from fluorescent emissions from a fluorescent substance that marks areas of functional interest.

System Identification, Environmental Modelling, and Control System Design

CERN Document Server

Garnier, Hugues

2012-01-01

System Identification, Environmetric Modelling, and Control Systems Design is dedicated to Professor Peter Young on the occasion of his seventieth birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume is comprised of a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as ...

Secret-key and identification rates for biometric identification systems with protected templates

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.

2010-01-01

In this paper we consider secret generation in biometric identification systems with protected templates. This problem is closely related to the study of the bio metric identification capacity [Willems et al., 2003] and [O’Sullivan and Sclmmid, 2002] and the common randomness generation scheme

New Waste Beverage Cans Identification Method

Directory of Open Access Journals (Sweden)

Firmansyah Burlian

2016-05-01

Full Text Available The primary emphasis of this work is on the development of a new waste beverage cans identification method for automated beverage cans sorting systems known as the SVS system. The method described involved window-based subdivision of the image into X-cells, construction of X-candidate template for N-cells, calculation of matching scores of reference templates for the N-cells image, and application of matching score to identify the grade of the object. The SVS system performance for correct beverage cans grade identification is 95.17% with estimated throughput of 21,600 objects per hour with a conveyor belt width of 18˝. The weight of the throughput depends on the size and type of the objects.

Closed-loop Identification for Control of Linear Parameter Varying Systems

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Trangbæk, Klaus

2014-01-01

, closed- loop system identification is more difficult than open-loop identification. In this paper we prove that the so-called Hansen Scheme, a technique known from linear time-invariant systems theory for transforming closed-loop system identification problems into open-loop-like problems, can...

Subspace identification of distributed clusters of homogeneous systems

NARCIS (Netherlands)

Yu, C.; Verhaegen, M.H.G.

2017-01-01

This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single

Image restoration for civil engineering structure monitoring using imaging system embedded on UAV

Science.gov (United States)

Vozel, Benoit; Dumoulin, Jean; Chehdi, Kacem

2013-04-01

Nowadays, civil engineering structures are periodically surveyed by qualified technicians (i.e. alpinist) operating visual inspection using heavy mechanical pods. This method is far to be safe, not only for civil engineering structures monitoring staff, but also for users. Due to the unceasing traffic increase, making diversions or closing lanes on bridge becomes more and more difficult. New inspection methods have to be found. One of the most promising technique is to develop inspection method using images acquired by a dedicated monitoring system operating around the civil engineering structures, without disturbing the traffic. In that context, the use of images acquired with an UAV, which fly around the structures is of particular interest. The UAV can be equipped with different vision system (digital camera, infrared sensor, video, etc.). Nonetheless, detection of small distresses on images (like cracks of 1 mm or less) depends on image quality, which is sensitive to internal parameters of the UAV (vibration modes, video exposure times, etc.) and to external parameters (turbulence, bad illumination of the scene, etc.). Though progresses were made at UAV level and at sensor level (i.e. optics), image deterioration is still an open problem. These deteriorations are mainly represented by motion blur that can be coupled with out-of-focus blur and observation noise on acquired images. In practice, deteriorations are unknown if no a priori information is available or dedicated additional instrumentation is set-up at UAV level. Image restoration processing is therefore required. This is a difficult problem [1-3] which has been intensively studied over last decades [4-12]. Image restoration can be addressed by following a blind approach or a myopic one. In both cases, it includes two processing steps that can be implemented in sequential or alternate mode. The first step carries out the identification of the blur impulse response and the second one makes use of this

Investigating the relationship between the practice of pharmaceutical care, construed external image, organizational identification, and job turnover intention of community pharmacists.

Science.gov (United States)

O'Neill, Jessica L; Gaither, Caroline A

2007-12-01

Pharmacy employers are being challenged to recruit and retain qualified employees. Our study hypothesized that pharmacists who practice pharmaceutical care have an attractive construed external image (how employees think outsiders view their organization), which strengthens their organizational identification (perceptions of oneness with or belongingness to the organization) and decreases job turnover intention (thoughts of quitting/searching for another job). A 7-page questionnaire was mailed to the homes of a random sample of 759 licensed pharmacists practicing in the United States. Participants had the option of returning the completed survey via postal mail or a Web site. The study variables were measured with previously validated scales. Structural equation modeling with latent variables evaluated the hypothesized relationships. Several demographic variables were included. Responses were received from 252 subjects (33%); 121 were community pharmacists. As hypothesized, organizational identification and job turnover intention were significantly related (B=-0.24) as well as construed external image and organizational identification (B=0.41). The practice of pharmaceutical care and construed external image were not significantly correlated (B=0.10). Although not hypothesized, construed external image was directly related to job turnover intention (B=-0.25). The effects of the practice of pharmaceutical care on job turnover intention were mediated through organizational identification. Position had significant effects. One additional benefit to the practice of pharmaceutical care may be strengthened organizational identification. Pharmacists' perception of the image of their employer may increase organizational identification and decrease job turnover intention. An understanding of the organizational identification of pharmacists would be useful in decreasing job turnover intention. Given the current demand for pharmacists, this is a worthwhile endeavor. Future

Evaluation of the utility of a glycemic pattern identification system.

Science.gov (United States)

Otto, Erik A; Tannan, Vinay

2014-07-01

With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes. To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows. Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification. The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control. © 2014 Diabetes Technology Society.

Spatial resolution limit study of a CCD camera and scintillator based neutron imaging system according to MTF determination and analysis

International Nuclear Information System (INIS)

Kharfi, F.; Denden, O.; Bourenane, A.; Bitam, T.; Ali, A.

2012-01-01

Spatial resolution limit is a very important parameter of an imaging system that should be taken into consideration before examination of any object. The objectives of this work are the determination of a neutron imaging system's response in terms of spatial resolution. The proposed procedure is based on establishment of the Modulation Transfer Function (MTF). The imaging system being studied is based on a high sensitivity CCD neutron camera (2×10 −5 lx at f1.4). The neutron beam used is from the horizontal beam port (H.6) of the Algerian Es-Salam research reactor. Our contribution is on the MTF determination by proposing an accurate edge identification method and a line spread function undersampling problem-resolving procedure. These methods and procedure are integrated into a MatLab code. The methods, procedures and approaches proposed in this work are available for any other neutron imaging system and allow for judging the ability of a neutron imaging system to produce spatial (internal details) properties of any object under examination. - Highlights: ► Determination of spatial response of a neutron imaging system. ► Ability of a neutron imaging system to reproduce spatial properties of any object. ► Spatial resolution limits measurement using MTF with the slanted edge method. ► Accurate edge identification and line spread function sampling improvement. ► Development of a MatLab code to compute automatically the MTF.

Quantitative image cytometry measurements of lipids, DNA, CD45 and cytokeratin for circulating tumor cell identification in a model system

Science.gov (United States)

Futia, Gregory L.; Qamar, Lubna; Behbakht, Kian; Gibson, Emily A.

2016-04-01

Circulating tumor cell (CTC) identification has applications in both early detection and monitoring of solid cancers. The rarity of CTCs, expected at ~1-50 CTCs per million nucleated blood cells (WBCs), requires identifying methods based on biomarkers with high sensitivity and specificity for accurate identification. Discovery of biomarkers with ever higher sensitivity and specificity to CTCs is always desirable to potentially find more CTCs in cancer patients thus increasing their clinical utility. Here, we investigate quantitative image cytometry measurements of lipids with the biomarker panel of DNA, Cytokeratin (CK), and CD45 commonly used to identify CTCs. We engineered a device for labeling suspended cell samples with fluorescent antibodies and dyes. We used it to prepare samples for 4 channel confocal laser scanning microscopy. The total data acquired at high resolution from one sample is ~ 1.3 GB. We developed software to perform the automated segmentation of these images into regions of interest (ROIs) containing individual cells. We quantified image features of total signal, spatial second moment, spatial frequency second moment, and their product for each ROI. We performed measurements on pure WBCs, cancer cell line MCF7 and mixed samples. Multivariable regressions and feature selection were used to determine combination features that are more sensitive and specific than any individual feature separately. We also demonstrate that computation of spatial characteristics provides higher sensitivity and specificity than intensity alone. Statistical models allowed quantification of the required sensitivity and specificity for detecting small levels of CTCs in a human blood sample.

Application of identification techniques to remote manipulator system flight data

Science.gov (United States)

Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

1983-01-01

This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

A portable air jet actuator device for mechanical system identification

Science.gov (United States)

Belden, Jesse; Staats, Wayne L.; Mazumdar, Anirban; Hunter, Ian W.

2011-03-01

System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon—the Coandă effect—is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use.

System identification on two-phase flow stability

International Nuclear Information System (INIS)

Wu Shaorong; Zhang Youjie; Wang Dazhong; Bo Jinghai; Wang Fei

1996-01-01

The theoretical principle, experimental method and results of interrelation analysis identification for the instability of two-phase flow are described. A completely new concept of test technology and method on two-phase flow stability was developed by using he theory of information science on system stability and system identification for two-phase flow stability in thermo-physics field. Application of this method would make it possible to identify instability boundary of two-phase flow under stable operation conditions of two-phase flow system. The experiment was carried out on the thermohydraulic test system HRTL-5. Using reverse repeated pseudo-random sequences of heating power as input signal sources and flow rate as response function in the test, the two-phase flow stability and stability margin of the natural circulation system are investigated. The effectiveness and feasibility of identifying two-phase flow stability by using this system identification method were experimentally demonstrated. Basic data required for mathematics modeling of two-phase flow and analysis of two-phase flow stability were obtained, which are useful for analyzing, monitoring of the system operation condition, and forecasting of two-phase flow stability in engineering system

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

Science.gov (United States)

Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

2016-07-12

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

Directory of Open Access Journals (Sweden)

Ángel Jesús Molina-Viedma

2018-02-01

Full Text Available The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC.

Science.gov (United States)

Molina-Viedma, Ángel Jesús; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A

2018-02-05

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

Science.gov (United States)

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Identification of fractional-order systems with unknown initial values and structure

Energy Technology Data Exchange (ETDEWEB)

Du, Wei, E-mail: duwei0203@gmail.com [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Miao, Qingying, E-mail: qymiao@sjtu.edu.cn [School of Continuing Education, Shanghai Jiao Tong University, Shanghai 200030 (China); Tong, Le, E-mail: tongle0328@gmail.com [Faculty of Applied Science and Textiles, The Hong Kong Polytechnic University, Hong Kong (China); Tang, Yang [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China)

2017-06-21

In this paper, the identification problem of fractional-order chaotic systems is proposed and investigated via an evolutionary optimization approach. Different with other studies to date, this research focuses on the identification of fractional-order chaotic systems with not only unknown orders and parameters, but also unknown initial values and structure. A group of fractional-order chaotic systems, i.e., Lorenz, Lü, Chen, Rössler, Arneodo and Volta chaotic systems, are set as the system candidate pool. The identification problem of fractional-order chaotic systems in this research belongs to mixed integer nonlinear optimization in essence. A powerful evolutionary algorithm called composite differential evolution (CoDE) is introduced for the identification problem presented in this paper. Extensive experiments are carried out to show that the fractional-order chaotic systems with unknown initial values and structure can be successfully identified by means of CoDE. - Highlights: • Unknown initial values and structure are introduced in the identification of fractional-order chaotic systems; • Only a series of output is utilized in the identification of fractional-order chaotic systems; • CoDE is used for the identification problem and the results are satisfactory when compared with other DE variants.

Quality study of portal images acquired by computed radiography and screen-film system under megavoltage ray

International Nuclear Information System (INIS)

Cao Guoquan; Jin Xiance; Wu Shixiu; Xie Congying; Zhang Li; Yu Jianyi; Li Yueqing

2007-01-01

Objective: To evaluate the quality of the portal images acquired by computed radiography (CR) system and conventional screen-film system, respectively. Methods: Imaging plates (IP) and X-ray films ora home-devised lead phantom with a leakage of 6.45% were acquired, and modulation transfer function (MTF) curves of the both images were measured using edge method. Portal images of 40 nasopharyngeal cancer patients were acquired by IP and screen-film system respectively. Two doctors with similar experience evaluated the damage degree of petrosal bone, the receiver operating characteristic (ROC) curve of CR images and general images were drawn according to two doctors evaluation results. Results: The identification frequency of CR system and screen-film system were 1.159 and 0.806 Lp/mm respectively. For doctor one, the area under ROC curve of CR images and general images were 0.802 and 0.742 respectively. For doctor two, the area under ROC curve of CR images and general images were 0.751 and 0.600 respectively. The MTF curve and ROC curve of CR are both better than those of screen-film system. Conclusion: The image quality of CR portal imaging is much better than that of screen-film system. The utility of CR in linear accelerator for portal imaging is promising in clinic. (authors)

Medical imaging systems

Science.gov (United States)

Frangioni, John V

2013-06-25

A medical imaging system provides simultaneous rendering of visible light and diagnostic or functional images. The system may be portable, and may include adapters for connecting various light sources and cameras in open surgical environments or laparascopic or endoscopic environments. A user interface provides control over the functionality of the integrated imaging system. In one embodiment, the system provides a tool for surgical pathology.

LPV system identification using series expansion models

NARCIS (Netherlands)

Toth, R.; Heuberger, P.S.C.; Hof, Van den P.M.J.; Santos, dos P.L.; Perdicoúlis, T.P.A.; Novara, C.; Ramos, J.A.; Rivera, D.E.

2011-01-01

This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. Written by world renowned researchers, the book contains twelve chapters, focusing on the most recent LPV identification methods for both discrete-time and continuous-time models, using different

[Comparation on Haversian system between human and animal bones by imaging analysis].

Science.gov (United States)

Lu, Hui-Ling; Zheng, Jing; Yao, Ya-Nan; Chen, Sen; Wang, Hui-Pin; Chen, Li-Xian; Guo, Jing-Yuan

2006-04-01

To explore the differences in Haversian system between human and animal bones through imaging analysis and morphology description. Thirty-five slices grinding from human being as well as dog, pig, cow and sheep bones were observed to compare their structure, then were analysed with the researchful microscope. Plexiform bone or oeston band was not found in human bones; There were significant differences in the shape, size, location, density of Haversian system, between human and animal bones. The amount of Haversian lamella and diameter of central canal in human were the biggest; Significant differences in the central canal diameter and total area percentage between human and animal bones were shown by imaging analysis. (1) Plexiform bone and osteon band could be the exclusive index in human bone; (2) There were significant differences in the structure of Haversian system between human and animal bones; (3) The percentage of central canals total area was valuable in species identification through imaging analysis.

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

Hyungchul Yoon

2017-09-01

Full Text Available Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc. are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1 estimation of an appropriate scale factor; and (2 compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

Science.gov (United States)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

Directory of Open Access Journals (Sweden)

Núbia Rosa da Silva

Full Text Available The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

WATERSHED ALGORITHM BASED SEGMENTATION FOR HANDWRITTEN TEXT IDENTIFICATION

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P. Mathivanan

2014-02-01

Full Text Available In this paper we develop a system for writer identification which involves four processing steps like preprocessing, segmentation, feature extraction and writer identification using neural network. In the preprocessing phase the handwritten text is subjected to slant removal process for segmentation and feature extraction. After this step the text image enters into the process of noise removal and gray level conversion. The preprocessed image is further segmented by using morphological watershed algorithm, where the text lines are segmented into single words and then into single letters. The segmented image is feature extracted by Daubechies’5/3 integer wavelet transform to reduce training complexity [1, 6]. This process is lossless and reversible [10], [14]. These extracted features are given as input to our neural network for writer identification process and a target image is selected for each training process in the 2-layer neural network. With the several trained output data obtained from different target help in text identification. It is a multilingual text analysis which provides simple and efficient text segmentation.

Mouse estrous cycle identification tool and images.

Directory of Open Access Journals (Sweden)

Shannon L Byers

Full Text Available The efficiency of producing timed pregnant or pseudopregnant mice can be increased by identifying those in proestrus or estrus. Visual observation of the vagina is the quickest method, requires no special equipment, and is best used when only proestrus or estrus stages need to be identified. Strain to strain differences, especially in coat color can make it difficult to determine the stage of the estrous cycle accurately by visual observation. Presented here are a series of images of the vaginal opening at each stage of the estrous cycle for 3 mouse strains of different coat colors: black (C57BL/6J, agouti (CByB6F1/J and albino (BALB/cByJ. When all 4 stages (proestrus, estrus, metestrus, and diestrus need to be identified, vaginal cytology is regarded as the most accurate method. An identification tool is presented to aid the user in determining the stage of estrous when using vaginal cytology. These images and descriptions are an excellent resource for learning how to determine the stage of the estrous cycle by visual observation or vaginal cytology.

Adaptive Colour Feature Identification in Image for Object Tracking

Directory of Open Access Journals (Sweden)

Feng Su

2012-01-01

Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

Improved Stochastic Subspace System Identification for Structural Health Monitoring

Science.gov (United States)

Chang, Chia-Ming; Loh, Chin-Hsiung

2015-07-01

Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes. The stochastic subspace system identification has been recognized as a power tool which can present a structure in the modal coordinates. To obtain qualitative identified data, this tool needs to spend computational expense on a large set of measurements. In study, a stochastic system identification framework is proposed to improve the efficiency and quality of the conventional stochastic subspace system identification. This framework includes 1) measured signal processing, 2) efficient space projection, 3) system order selection, and 4) modal property derivation. The measured signal processing employs the singular spectrum analysis algorithm to lower the noise components as well as to present a data set in a reduced dimension. The subspace is subsequently derived from the data set presented in a delayed coordinate. With the proposed order selection criteria, the number of structural modes is determined, resulting in the modal properties. This system identification framework is applied to a real-world bridge for exploring the feasibility in real-time applications. The results show that this improved system identification method significantly decreases computational time, while qualitative modal parameters are still attained.

Panoramic, Macro and Micro Multispectral Imaging: An Affordable System for Mapping Pigments on Artworks

Directory of Open Access Journals (Sweden)

Antonino Cosentino

2015-07-01

Full Text Available Multispectral imaging systems are used in art examinations to map and identify pigments, binders and areas of retouching. A monochromatic camera is combined with an appropriate wavelength selection system and acquires a variable number of spectral images of a scene. These images are then stacked into a reflectance imaging cube to reconstruct reflectance spectra from each of the images’ pixels. This paper presents an affordable multispectral imaging system composed of a monochromatic CCD camera and a set of only 12 interference filters for mapping pigments on works of art and for the tentative identification of such pigments. This work demonstrates the versatility of this set-up, a versatility enabling it to be applied to different tasks, involving examination and documentation of objects of varying size. Use of this multispectral camera for both panoramic and macro photography is discussed, together with the possibilities facilitated from the coupling of the system to a stereomicroscope and a compound microscope. This system is of particular interest for the cultural heritage sector because of its hardware simplicity and acquisition speed, as well as its lightness and small dimensions.

Coal Layer Identification using Electrical Resistivity Imaging Method in Sinjai Area South Sulawesi

Science.gov (United States)

Ilham Samanlangi, Andi

2018-03-01

The purpose of this research is to image subsurface resistivity for coal identification in Panaikang Village, Sinjai, South Sulawesi.Resistivity measurements were conducted in 3 lines of length 400 meters and 300 meter using resistivity imaging, dipole-dipole configuration. Resistivity data was processed using Res2DInv software to image resistivity variation and interpret lithology. The research results shown that coal resistivity in Line is about 70-200 Ωm, Line 2 is about 70-90 Ωm, and Line 3 is about 70-200 Ωm with average thickness about 10 meters and distributed to the east of research area.

Lineament systems indentification in Banten site using Spot 5 satellite image

International Nuclear Information System (INIS)

Yuliastuti; Heni Susiati; Yunus Daud; A-Sarwiyana Sastratenaya

2013-01-01

Lineament systems identification in Banten site using SPOT 5 satellite image has been performed. Based on regional site survey in Java Island, Banten is one of the potential candidate sites. The objective of this study was to determine direction and chronology of regional lineament morphology which was consider as fault or faulting in Banten site. The methodology used this study covered satellite image cropping, band selection, edge enhancement filtering, lineament extraction and lineament analysis. Result of the study showed that there were three dominant lineament groups, namely N-S, NW-SE, and E-W. Based on the forming chronology of the lineament, N-S group was the oldest one, followed by E-W group and NW-SE as the youngest group. These lineament groups have been confirmed as a manifestation of fault system structure. (author)

System Identification Methods for Aircraft Flight Control Development and Validation

Science.gov (United States)

1995-10-01

System-identification methods compose a mathematical model, or series of models, : from measurements of inputs and outputs of dynamic systems. This paper : discusses the use of frequency-domain system-identification methods for the : development and ...

Design of biometrics identification system on palm vein using infrared light

Science.gov (United States)

Syafiq, Muhammad; Nasution, Aulia M. T.

2016-11-01

Image obtained by the LED with wavelength 740nm and 810nm showed that the contrast gradient of vein pattern is low and palm pattern still exist. It means that 740nm and 810nm are less suitable for the detection of blood vessels in the palm of the hand. At a wavelength of 940nm, the pattern is clearly visible, and the pattern of the palms is mostly gone. Furthermore, the pre-processing performed using smoothing process which include Gaussian filter and median filter and contrast stretching. Image segmentation is done by getting the ROI area that would be obtained its information. The identification process of image features obtained by using MSE (Mean Suare Error) method ,LBP (Local Binary Pattern). Furthermore, we will use a database consists of 5 different palm vein pattern which will be used for testing the tool in the identification process. All the process above are done using Raspberry Pi device. The Obtained MSE parameter is 0.025 and LBP features score are less than 10-3 for image to be matched.

Active thermography and post-processing image enhancement for recovering of abraded and paint-covered alphanumeric identification marks

Science.gov (United States)

Montanini, R.; Quattrocchi, A.; Piccolo, S. A.

2016-09-01

Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery of the lost data many destructive or non-destructive techniques have been endeavoured so far, which however present several restrictions. In this paper, active infrared thermography has been exploited for the first time in order to assess its effectiveness in restoring paint covered and abraded labels made by means of different manufacturing processes (laser, dot peen, impact, cold press and scribe). Optical excitation of the target surface has been achieved using pulse (PT), lock-in (LT) and step heating (SHT) thermography. Raw infrared images were analysed with a dedicated image processing software originally developed in Matlab™, exploiting several methods, which include thermographic signal reconstruction (TSR), guided filtering (GF), block guided filtering (BGF) and logarithmic transformation (LN). Proper image processing of the raw infrared images resulted in superior contrast and enhanced readability. In particular, for deeply abraded marks, good outcomes have been obtained by application of logarithmic transformation to raw PT images and block guided filtering to raw phase LT images. With PT and LT it was relatively easy to recover labels covered by paint, with the latter one providing better thermal contrast for all the examined targets. Step heating thermography never led to adequate label identification instead.

Improved system blind identification based on second-order ...

Indian Academy of Sciences (India)

An improved system blind identification method based on second- order cyclostationary statistics and the properties of group delay, has been ... In the last decade, there has been considerable research on achieving blind identification.

The Establishment of the SAR images database System Based on Oracle and ArcSDE

International Nuclear Information System (INIS)

Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

2014-01-01

Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

PARAMETRIC IDENTIFICATION OF STOCHASTIC SYSTEM BY NON-GRADIENT RANDOM SEARCHING

Directory of Open Access Journals (Sweden)

A. A. Lobaty

2017-01-01

Full Text Available At this moment we know a great variety of identification objects, tasks and methods and its significance is constantly increasing in various fields of science and technology.  The identification problem is dependent on a priori information about identification object, besides that  the existing approaches and methods of identification are determined by the form of mathematical models (deterministic, stochastic, frequency, temporal, spectral etc.. The paper considers a problem for determination of system parameters  (identification object which is assigned by the stochastic mathematical model including random functions of time. It has been shown  that while making optimization of the stochastic systems subject to random actions deterministic methods can be applied only for a limited approximate optimization of the system by taking into account average random effects and fixed structure of the system. The paper proposes an algorithm for identification of  parameters in a mathematical model of  the stochastic system by non-gradient random searching. A specific  feature  of the algorithm is its applicability  practically to mathematic models of any type because the applied algorithm does not depend on linearization and differentiability of functions included in the mathematical model of the system. The proposed algorithm  ensures searching of  an extremum for the specified quality criteria in terms of external uncertainties and limitations while using random searching of parameters for a mathematical model of the system. The paper presents results of the investigations on operational capability of the considered identification method  while using mathematical simulation of hypothetical control system with a priori unknown parameter values of the mathematical model. The presented results of the mathematical simulation obviously demonstrate the operational capability of the proposed identification method.

Integrated manufacture of a freeform off-axis multi-reflective imaging system without optical alignment.

Science.gov (United States)

Li, Zexiao; Liu, Xianlei; Fang, Fengzhou; Zhang, Xiaodong; Zeng, Zhen; Zhu, Linlin; Yan, Ning

2018-03-19

Multi-reflective imaging systems find wide applications in optical imaging and space detection. However, it is faced with difficulties in adjusting the freeform mirrors with high accuracy to guarantee the optical function. Motivated by this, an alignment-free manufacture approach is proposed to machine the optical system. The direct optical performance-guided manufacture route is established without measuring the form error of freeform optics. An analytical model is established to investigate the effects of machine errors to serve the error identification and compensation in machining. Based on the integrated manufactured system, an ingenious self-designed testing configuration is constructed to evaluate the optical performance by directly measuring the wavefront aberration. Experiments are carried out to manufacture a three-mirror anastigmat, surface topographical details and optical performance shows agreement to the designed expectation. The final system works as an off-axis infrared imaging system. Results validate the feasibility of the proposed method to achieve excellent optical application.

SORIS—A standoff radiation imaging system

Science.gov (United States)

Zelakiewicz, Scott; Hoctor, Ralph; Ivan, Adrian; Ross, William; Nieters, Edward; Smith, William; McDevitt, Daniel; Wittbrodt, Michael; Milbrath, Brian

2011-10-01

The detection of radiological and special nuclear material within the country's borders is a crucial component of the national security network. Being able to detect small amounts of radiological material at large distances is especially important for search applications. To provide this capability General Electric's Research Center has developed, as a part of DNDO's standoff radiation detection system advanced technology demonstration (SORDS-ATD) program, a standoff radiation imaging system (SORIS). This vehicle-based system is capable of detecting weak sources at large distances in relatively short times. To accomplish this, GE has developed a novel coded aperture detector based on commercial components from GE Healthcare. An array of commercial gamma cameras modified to increase the system efficiency and energy range are used as position sensitive detectors. Unlike typical coded aperture systems, however, SORIS employs a non-planar mask and thus does not suffer the typical limitations of partially encoded regions giving it a wide field of view. Source identification is done using both low-statistics anomaly indicators and conventional high-statistics algorithms being developed by Pacific Northwest National Laboratory. The results of scanned areas and threats identified are displayed to the user and overlaid on satellite imagery.

SORIS-A standoff radiation imaging system

International Nuclear Information System (INIS)

Zelakiewicz, Scott; Hoctor, Ralph; Ivan, Adrian; Ross, William; Nieters, Edward; Smith, William; McDevitt, Daniel; Wittbrodt, Michael; Milbrath, Brian

2011-01-01

The detection of radiological and special nuclear material within the country's borders is a crucial component of the national security network. Being able to detect small amounts of radiological material at large distances is especially important for search applications. To provide this capability General Electric's Research Center has developed, as a part of DNDO's standoff radiation detection system advanced technology demonstration (SORDS-ATD) program, a standoff radiation imaging system (SORIS). This vehicle-based system is capable of detecting weak sources at large distances in relatively short times. To accomplish this, GE has developed a novel coded aperture detector based on commercial components from GE Healthcare. An array of commercial gamma cameras modified to increase the system efficiency and energy range are used as position sensitive detectors. Unlike typical coded aperture systems, however, SORIS employs a non-planar mask and thus does not suffer the typical limitations of partially encoded regions giving it a wide field of view. Source identification is done using both low-statistics anomaly indicators and conventional high-statistics algorithms being developed by Pacific Northwest National Laboratory. The results of scanned areas and threats identified are displayed to the user and overlaid on satellite imagery.

Implementation of an Imaging Spectrometer for Localization and Identification of Radioactive Sources

International Nuclear Information System (INIS)

Hermine, Lemaire; Carrel, Frederick; Gmar, Mehdi; Menesguen Yves; Normand, Stephane; Schoepff, Vincent; Abou-Khalil, Roger; Amgarou, Khalil; Menaa, Nabil; Tebug, Timi; Angelique, Jean-Claude; Bonnet, Florent; De-Toro, Daniel; Giarmana, Olivier; Patoz, Audrey; Talent, Philippe

2013-06-01

Spatial localization of radioactive sources is currently a main issue interesting nuclear industry as well as homeland security applications, and can be achieved using gamma cameras. For several years, CEA LIST has been designing a new system, called GAMPIX, with improved sensitivity, portability and ease of use. The main remaining limitation is the lack of spectrometric information, preventing radioactive materials identification. This article describes the development of an imaging spectrometer based on the GAMPIX technology. Experimental tests have been carried out according to both spectrometric methods enabled by the pixelated Timepix readout chip used in the GAMPIX gamma camera. The first method is based on the size of the impacts produced by a gamma-ray energy deposition in the detection matrix. The second one uses the Time over Threshold (ToT) mode of the Timepix chip and deals with time spent by pulses generated by charge preamplifiers over a user-specified threshold. Both energy resolution and sensitivity studies proved the superiority of the ToT approach that will consequently be further explored. Energy calibration, tests of several pixel sizes and use of the Medipix3 readout chip are tracks to improve performances of the newly implemented imaging spectrometer. (authors)

Performance of an optical identification and interrogation system

Science.gov (United States)

Venugopalan, A.; Ghosh, A. K.; Verma, P.; Cheng, S.

2008-04-01

A free space optics based identification and interrogation system has been designed. The applications of the proposed system lie primarily in areas which require a secure means of mutual identification and information exchange between optical readers and tags. Conventional RFIDs raise issues regarding security threats, electromagnetic interference and health safety. The security of RF-ID chips is low due to the wide spatial spread of radio waves. Malicious nodes can read data being transmitted on the network, if they are in the receiving range. The proposed system provides an alternative which utilizes the narrow paraxial beams of lasers and an RSA-based authentication scheme. These provide enhanced security to communication between a tag and the base station or reader. The optical reader can also perform remote identification and the tag can be read from a far off distance, given line of sight. The free space optical identification and interrogation system can be used for inventory management, security systems at airports, port security, communication with high security systems, etc. to name a few. The proposed system was implemented with low-cost, off-the-shelf components and its performance in terms of throughput and bit error rate has been measured and analyzed. The range of operation with a bit-error-rate lower than 10-9 was measured to be about 4.5 m. The security of the system is based on the strengths of the RSA encryption scheme implemented using more than 1024 bits.

Identification of general linear mechanical systems

Science.gov (United States)

Sirlin, S. W.; Longman, R. W.; Juang, J. N.

1983-01-01

Previous work in identification theory has been concerned with the general first order time derivative form. Linear mechanical systems, a large and important class, naturally have a second order form. This paper utilizes this additional structural information for the purpose of identification. A realization is obtained from input-output data, and then knowledge of the system input, output, and inertia matrices is used to determine a set of linear equations whereby we identify the remaining unknown system matrices. Necessary and sufficient conditions on the number, type and placement of sensors and actuators are given which guarantee identificability, and less stringent conditions are given which guarantee generic identifiability. Both a priori identifiability and a posteriori identifiability are considered, i.e., identifiability being insured prior to obtaining data, and identifiability being assured with a given data set.

Biometric identification using local iterated function

Science.gov (United States)

Al-Saidi, N. M. G.; Said, M. R. M.

2014-06-01

Biometric identification protocol has been received an increasing interest recently. It is a process that determines person identity by making use of their biometric features. A new biometric identification method is presented in this paper based on partial self-similarity that used to identify features within fingerprint images. This approach is already used in Fractal Image Compression (FIC) due to their ability to represent the images by a limited number of affine transformations, and its variation of scale, translation or rotation. These features give the recognition process high impact and good performance. To process data in a fingerprint image, it first converted into digital format using Optical Fingerprint Reader (OFR). The verification process is done by comparing these data with the server data. The system analysis shows that the proposed method is efficient in terms of memory and time complexity.

An Automated System for Garment Texture Design Class Identification

Directory of Open Access Journals (Sweden)

Emon Kumar Dey

2015-09-01

Full Text Available Automatic identification of garment design class might play an important role in the garments and fashion industry. To achieve this, essential initial works are found in the literature. For example, construction of a garment database, automatic segmentation of garments from real life images, categorizing them into the type of garments such as shirts, jackets, tops, skirts, etc. It is now essential to find a system such that it will be possible to identify the particular design (printed, striped or single color of garment product for an automated system to recommend the garment trends. In this paper, we have focused on this specific issue and thus propose two new descriptors namely Completed CENTRIST (cCENTRIST and Ternary CENTRIST (tCENTRIST. To test these descriptors, we used two different publically available databases. The experimental results of these databases demonstrate that both cCENTRIST and tCENTRIST achieve nearly about 3% more accuracy than the existing state-of-the art methods.

Modeling of Biometric Identification System Using the Colored Petri Nets

Science.gov (United States)

Petrosyan, G. R.; Ter-Vardanyan, L. A.; Gaboutchian, A. V.

2015-05-01

In this paper we present a model of biometric identification system transformed into Petri Nets. Petri Nets, as a graphical and mathematical tool, provide a uniform environment for modelling, formal analysis, and design of discrete event systems. The main objective of this paper is to introduce the fundamental concepts of Petri Nets to the researchers and practitioners, both from identification systems, who are involved in the work in the areas of modelling and analysis of biometric identification types of systems, as well as those who may potentially be involved in these areas. In addition, the paper introduces high-level Petri Nets, as Colored Petri Nets (CPN). In this paper the model of Colored Petri Net describes the identification process much simpler.

Image reconstruction of dynamic infrared single-pixel imaging system

Science.gov (United States)

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

2018-03-01

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

A device for identification of respective images in orthogonal localization roentgenograms

International Nuclear Information System (INIS)

Ganchev, M.

1977-01-01

Some problems which might be solved with the device, originally intended for localization of implanted radioactive wires, include: conjugation check-up of orthogonal localization roentgenograms; localization of partially screened radioactive sources in the patient body; localization of Fletcher's trapezium points in the pelvis; identification of the respective images of contrast filled lymph nodes and localization of some bone hallmarks, visible only on one of two localization roentgenograms. (author)

Optimized Experiment Design for Marine Systems Identification

DEFF Research Database (Denmark)

Blanke, M.; Knudsen, Morten

1999-01-01

Simulation of maneuvring and design of motion controls for marine systems require non-linear mathematical models, which often have more than one-hundred parameters. Model identification is hence an extremely difficult task. This paper discusses experiment design for marine systems identification...... and proposes a sensitivity approach to solve the practical experiment design problem. The applicability of the sensitivity approach is demonstrated on a large non-linear model of surge, sway, roll and yaw of a ship. The use of the method is illustrated for a container-ship where both model and full-scale tests...

Page segmentation using script identification vectors: A first look

Energy Technology Data Exchange (ETDEWEB)

Hochberg, J.; Cannon, M.; Kelly, P.; White, J.

1997-07-01

Document images in which different scripts, such as Chinese and Roman, appear on a single page pose a problem for optical character recognition (OCR) systems. This paper explores the use of script identification vectors in the analysis of multilingual document images. A script identification vector is calculated for each connected component in a document. The vector expresses the closest distance between the component and templates developed for each of thirteen scripts, including Arabic, Chinese, Cyrillic, and Roman. The authors calculate the first three principal components within the resulting thirteen-dimensional space for each image. By mapping these components to red, green, and blue, they can visualize the information contained in the script identification vectors. The visualization of several multilingual images suggests that the script identification vectors can be used to segment images into script-specific regions as large as several paragraphs or as small as a few characters. The visualized vectors also reveal distinctions within scripts, such as font in Roman documents, and kanji vs. kana in Japanese. Results are best for documents containing highly dissimilar scripts such as Roman and Japanese. Documents containing similar scripts, such as Roman and Cyrillic will require further investigation.

Synchrotron FTIR Imaging For The Identification Of Cell Types Within Human Tissues

International Nuclear Information System (INIS)

Walsh, Michael J.; Pounder, F. Nell; Nasse, Michael J.; Macias, Virgilia; Kajdacsy-Balla, Andre; Hirschmugl, Carol; Bhargava, Rohit

2010-01-01

The use of synchrotron Fourier Transform Infrared spectroscopy (S-FTIR) has been shown to be a very promising tool for biomedical research. S-FTIR spectroscopy allows for the fast acquisition of infrared (IR) spectra at a spatial resolution approaching the IR diffraction limit. The development of the Infrared Environmental Imaging (IRENI) beamline at the Synchrotron Radiation Center (SRC) at the University of Wisconsin-Madison has allowed for diffraction limited imaging measurements of cells in human prostate and breast tissues. This has allowed for the identification of cell types within tissues that would otherwise not have been resolvable using conventional FTIR sources.

Identification of System Parameters by the Random Decrement Technique

DEFF Research Database (Denmark)

Brincker, Rune; Kirkegaard, Poul Henning; Rytter, Anders

1991-01-01

-Walker equations and finally, least-square fitting of the theoretical correlation function. The results are compared to the results of fitting an Auto Regressive Moving Average (ARMA) model directly to the system output from a single-degree-of-freedom system loaded by white noise.......The aim of this paper is to investigate and illustrate the possibilities of using correlation functions estimated by the Random Decrement Technique as a basis for parameter identification. A two-stage system identification system is used: first, the correlation functions are estimated by the Random...... Decrement Technique, and then the system parameters are identified from the correlation function estimates. Three different techniques are used in the parameter identification process: a simple non-parametric method, estimation of an Auto Regressive (AR) model by solving an overdetermined set of Yule...

Consumer–brand identification revisited: An integrative framework of brand identification, customer satisfaction, and price image and their role for brand loyalty and word of mouth

OpenAIRE

Popp, B; Woratschek, H

2017-01-01

Consumer–brand identification has received considerable attraction among scholars and practitioners in recent years. We contribute to previous research by proposing an integrative model that includes consumer–brand identification, customer satisfaction, and price image to investigate the interrelationships among these constructs as well as their effects on brand loyalty and positive word of mouth. To provide general results, we empirically test the model using a sample of 1443 respondents fro...

Identification system by eye retinal pattern

International Nuclear Information System (INIS)

Sunagawa, Takahisa; Shibata, Susumu

1987-01-01

Identification system by eye retinal pattern is introduced from the view-point of history of R and D, measurement, apparatus, evaluation tests, safety and application. According to our evaluation tests, enrolling time is approximately less than 1 min, verification time is a few seconds and false accept rate is 0 %. Evaluation tests at Sandia National Laboratories in USA show the comparison data of false accept rates such as 0 % for eye retinal pattern, 10.5 % for finger-print, 5.8 % for signature dynamics and 17.7 % for speaker voice. The identification system by eye retinal pattern has only three applications in Japan, but there has been a number of experience in USA. This fact suggests that the system will become an important means for physical protections not only in nuclear field but also in other industrial fields in Japan. (author)

Weed identification using an automated active shape matching (AASM) technique

DEFF Research Database (Denmark)

C. Swain, Kishore; Nørremark, Michael; Jørgensen, Rasmus Nyholm

2011-01-01

Weed identification and control is a challenge for intercultural operations in agriculture. As an alternative to chemical pest control, a smart weed identification technique followed by mechanical weed control system could be developed. The proposed smart identification technique works on the con......Weed identification and control is a challenge for intercultural operations in agriculture. As an alternative to chemical pest control, a smart weed identification technique followed by mechanical weed control system could be developed. The proposed smart identification technique works...... on the concept of ‘active shape modelling’ to identify weed and crop plants based on their morphology. The automated active shape matching system (AASM) technique consisted of, i) a Pixelink camera ii) an LTI (Lehrstuhlfuer technische informatik) image processing library, iii) a laptop pc with the Linux OS. A 2...

Biometric iris image acquisition system with wavefront coding technology

Science.gov (United States)

Hsieh, Sheng-Hsun; Yang, Hsi-Wen; Huang, Shao-Hung; Li, Yung-Hui; Tien, Chung-Hao

2013-09-01

Biometric signatures for identity recognition have been practiced for centuries. Basically, the personal attributes used for a biometric identification system can be classified into two areas: one is based on physiological attributes, such as DNA, facial features, retinal vasculature, fingerprint, hand geometry, iris texture and so on; the other scenario is dependent on the individual behavioral attributes, such as signature, keystroke, voice and gait style. Among these features, iris recognition is one of the most attractive approaches due to its nature of randomness, texture stability over a life time, high entropy density and non-invasive acquisition. While the performance of iris recognition on high quality image is well investigated, not too many studies addressed that how iris recognition performs subject to non-ideal image data, especially when the data is acquired in challenging conditions, such as long working distance, dynamical movement of subjects, uncontrolled illumination conditions and so on. There are three main contributions in this paper. Firstly, the optical system parameters, such as magnification and field of view, was optimally designed through the first-order optics. Secondly, the irradiance constraints was derived by optical conservation theorem. Through the relationship between the subject and the detector, we could estimate the limitation of working distance when the camera lens and CCD sensor were known. The working distance is set to 3m in our system with pupil diameter 86mm and CCD irradiance 0.3mW/cm2. Finally, We employed a hybrid scheme combining eye tracking with pan and tilt system, wavefront coding technology, filter optimization and post signal recognition to implement a robust iris recognition system in dynamic operation. The blurred image was restored to ensure recognition accuracy over 3m working distance with 400mm focal length and aperture F/6.3 optics. The simulation result as well as experiment validates the proposed code

Imaging systems in nuclear medicine and image evaluation

International Nuclear Information System (INIS)

Beck, R.; Charleston, D.; Metz, C.

1980-01-01

This project deals with imaging systems in nuclear medicine and image evaluation and is presented as four subprojects. The goal of the first subproject is to improve diagnositc image quality by development of a general computer code for optimizing collimator design. The second subproject deals with a secondary emission and fluorescence technique for thyroid scanning while the third subproject emphasizes the need for more sophisticated image processing systems such as coherent optical spatial filtering systems and digital image processing. The fourth subproject presents a new approach for processing image data by taking into account the energy of each detected gamma-ray photon

Variation in Microbial Identification System accuracy for yeast identification depending on commercial source of Sabouraud dextrose agar.

Science.gov (United States)

Kellogg, J A; Bankert, D A; Chaturvedi, V

1999-06-01

The accuracy of the Microbial Identification System (MIS; MIDI, Inc. ) for identification of yeasts to the species level was compared by using 438 isolates grown on prepoured BBL Sabouraud dextrose agar (SDA) and prepoured Remel SDA. Correct identification was observed for 326 (74%) of the yeasts cultured on BBL SDA versus only 214 (49%) of yeasts grown on Remel SDA (P < 0.001). The commercial source of the SDA used in the MIS procedure significantly influences the system's accuracy.

Structural system identification: Structural dynamics model validation

Energy Technology Data Exchange (ETDEWEB)

Red-Horse, J.R.

1997-04-01

Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

Mobile, hybrid Compton/coded aperture imaging for detection, identification and localization of gamma-ray sources at stand-off distances

Science.gov (United States)

Tornga, Shawn R.

The Stand-off Radiation Detection System (SORDS) program is an Advanced Technology Demonstration (ATD) project through the Department of Homeland Security's Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-SORDS Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 sodium iodide (NaI) crystals 5x5x2 in3 each, arranged in a random coded aperture mask array (CA), followed by 30 position sensitive NaI bars each 24x2.5x3 in3 called the detection array (DA). The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, developed coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than either alone. Since the TMI is a moving system, peripheral data, such as a Global Positioning System (GPS) and Inertial Navigation System (INS) must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the Geometry and Tracking Toolkit v4 (GEANT4). Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as

Image features dependant correlation-weighting function for efficient PRNU based source camera identification.

Science.gov (United States)

Tiwari, Mayank; Gupta, Bhupendra

2018-04-01

For source camera identification (SCI), photo response non-uniformity (PRNU) has been widely used as the fingerprint of the camera. The PRNU is extracted from the image by applying a de-noising filter then taking the difference between the original image and the de-noised image. However, it is observed that intensity-based features and high-frequency details (edges and texture) of the image, effect quality of the extracted PRNU. This effects correlation calculation and creates problems in SCI. For solving this problem, we propose a weighting function based on image features. We have experimentally identified image features (intensity and high-frequency contents) effect on the estimated PRNU, and then develop a weighting function which gives higher weights to image regions which give reliable PRNU and at the same point it gives comparatively less weights to the image regions which do not give reliable PRNU. Experimental results show that the proposed weighting function is able to improve the accuracy of SCI up to a great extent. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification and ultrastructural imaging of photodynamic therapy-induced microfilaments by atomic force microscopy

International Nuclear Information System (INIS)

Jung, Se-Hui; Park, Jin-Young; Yoo, Je-Ok; Shin, Incheol; Kim, Young-Myeong; Ha, Kwon-Soo

2009-01-01

Atomic force microscopy (AFM) is an emerging technique for imaging biological samples at subnanometer resolution; however, the method is not widely used for cell imaging because it is limited to analysis of surface topology. In this study, we demonstrate identification and ultrastructural imaging of microfilaments using new approaches based on AFM. Photodynamic therapy (PDT) with a new chlorin-based photosensitizer DH-II-24 induced cell shrinkage, membrane blebbing, and reorganization of cytoskeletons in bladder cancer J82 cells. We investigated cytoskeletal changes using confocal microscopy and atomic force microscopy. Extracellular filaments formed by PDT were analyzed with a tandem imaging approach based on confocal microscopy and atomic force microscopy. Ultrathin filaments that were not visible by confocal microscopy were identified as microfilaments by on-stage labeling/imaging using atomic force microscopy. Furthermore, ultrastructural imaging revealed that these microfilaments had a stranded helical structure. Thus, these new approaches were useful for ultrastructural imaging of microfilaments at the molecular level, and, moreover, they may help to overcome the current limitations of fluorescence-based microscopy and atomic force microscopy in cell imaging.

Particle identification at an asymmetric B Factory

International Nuclear Information System (INIS)

Coyle, P.; Eigen, G.; Hitlin, D.; Oddone, P.; Ratcliff, B.; Roe, N.; Va'vra, J.; Ypsilantis, T.

1991-09-01

Particle identification systems are an important component of any detector at a high-luminosity, asymmetric B Factory. In particular, excellent hadron identification is required to probe CP violation in B 0 decays to CP eigenstates. The particle identification systems discussed below also provide help in separating leptons from hadrons at low momenta. We begin this chapter with a discussion of the physics motivation for providing particle identification, the inherent limitations due to interactions and decays in flight, and the requirements for hermiticity and angular coverage. A special feature of an asymmetric B Factory is the resulting asymmetry in the momentum distribution as a function of polar angle; this will also be quantified and discussed. In the next section the three primary candidates, time-of-flight (TOF), energy loss (dE/dx), and Cerenkov counters, both ring-imaging and threshold, will be briefly described and evaluated. Following this, one of the candidates, a long-drift Cerenkov ring-imaging device, is described in detail to provide a reference design. Design considerations for a fast RICH are then described. A detailed discussion of aerogel threshold counter designs and associated R ampersand D conclude the chapter. 56 refs., 64 figs., 13 tabs

Identification of Nonlinear Dynamic Systems Possessing Some Non-linearities

Directory of Open Access Journals (Sweden)

Y. N. Pavlov

2015-01-01

Full Text Available The subject of this work is the problem of identification of nonlinear dynamic systems based on the experimental data obtained by applying test signals to the system. The goal is to determinate coefficients of differential equations of systems by experimental frequency hodographs and separate similar, but different, in essence, forces: dissipative forces with the square of the first derivative in the motion equations and dissipative force from the action of dry friction. There was a proposal to use the harmonic linearization method to approximate each of the nonlinearity of "quadratic friction" and "dry friction" by linear friction with the appropriate harmonic linearization coefficient.Assume that a frequency transfer function of the identified system has a known form. Assume as well that there are disturbances while obtaining frequency characteristics of the realworld system. As a result, the points of experimentally obtained hodograph move randomly. Searching for solution of the identification problem was in the hodograph class, specified by the system model, which has the form of the frequency transfer function the same as the form of the frequency transfer function of the system identified. Minimizing a proximity criterion (measure of the experimentally obtained system hodograph and the system hodograph model for all the experimental points described and previously published by one of the authors allowed searching for the unknown coefficients of the frequenc ransfer function of the system model. The paper shows the possibility to identify a nonlinear dynamic system with multiple nonlinearities, obtained on the experimental samples of the frequency system hodograph. The proposed algorithm allows to select the nonlinearity of the type "quadratic friction" and "dry friction", i.e. also in the case where the nonlinearity is dependent on the same dynamic parameter, in particular, on the derivative of the system output value. For the dynamic

SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

Energy Technology Data Exchange (ETDEWEB)

Jani, S; Low, D; Lamb, J [UCLA, Los Angeles, CA (United States)

2015-06-15

Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

International Nuclear Information System (INIS)

Jani, S; Low, D; Lamb, J

2015-01-01

Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

Skin image illumination modeling and chromophore identification for melanoma diagnosis

Science.gov (United States)

Liu, Zhao; Zerubia, Josiane

2015-05-01

The presence of illumination variation in dermatological images has a negative impact on the automatic detection and analysis of cutaneous lesions. This paper proposes a new illumination modeling and chromophore identification method to correct lighting variation in skin lesion images, as well as to extract melanin and hemoglobin concentrations of human skin, based on an adaptive bilateral decomposition and a weighted polynomial curve fitting, with the knowledge of a multi-layered skin model. Different from state-of-the-art approaches based on the Lambert law, the proposed method, considering both specular reflection and diffuse reflection of the skin, enables us to address highlight and strong shading effects usually existing in skin color images captured in an uncontrolled environment. The derived melanin and hemoglobin indices, directly relating to the pathological tissue conditions, tend to be less influenced by external imaging factors and are more efficient in describing pigmentation distributions. Experiments show that the proposed method gave better visual results and superior lesion segmentation, when compared to two other illumination correction algorithms, both designed specifically for dermatological images. For computer-aided diagnosis of melanoma, sensitivity achieves 85.52% when using our chromophore descriptors, which is 8~20% higher than those derived from other color descriptors. This demonstrates the benefit of the proposed method for automatic skin disease analysis.

Imaging system design and image interpolation based on CMOS image sensor

Science.gov (United States)

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

2009-11-01

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

Biometric identification systems: the science of transaction facilitation

Science.gov (United States)

Rogers, Robert R.

1994-10-01

The future ofthe "secure transaction" and the success ofall undertakings that depend on absolute certainty that the individuals involved really are who and what they represent themselves to be is dependent upon the successful development of absolutely accurate, low-cost and easy-to-operate Biometric Identification Systems. Whether these transactions are political, military, financial or administrative (e.g. health cards, drivers licenses, welfare entitlement, national identification cards, credit card transactions, etc.), the need for such secure and positive identification has never been greater -and yet we are only at the beginning ofan era in which we will see the emergence and proliferation of Biometric Identification Systems in nearly every field ofhuman endeavor. Proper application ofthese systems will change the way the world operates, and that is precisely the goal ofComparator Systems Corporation. Just as with the photo-copier 40 years ago and the personal computer 20 years ago, the potential applications for positive personal identification are going to make the Biometric Identification System a commonplace component in the standard practice ofbusiness, and in interhuman relationships ofall kinds. The development of new and specific application hardware, as well as the necessary algorithms and related software required for integration into existing operating procedures and newly developed systems alike, has been a more-than-a-decade-long process at Comparator -and we are now on the verge of delivering these systems to the world markets so urgently in need of them. An individual could feel extremely confident and satisfied ifhe could present his credit, debit, or ATM card at any point of sale and, after inserting his card, could simply place his finger on a glass panel and in less than a second be positively accepted as being the person that the card purported him to be; not to mention the security and satisfaction of the vendor involved in knowing that

A portable system for nuclear, chemical agent, and explosives identification

International Nuclear Information System (INIS)

Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.; Caffrey, A.J.

2001-01-01

The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electromechanically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine a prompt-gamma neutron-activation analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

A Portable System for Nuclear, Chemical Agent and Explosives Identification

International Nuclear Information System (INIS)

Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Caffrey, A.J.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.

2000-01-01

The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electrochemically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine an active neutron interrogation and analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

Ultrasonic sectional imaging for crack identification. Part 1. Confirmation test of essential factors for ultrasonic imaging

International Nuclear Information System (INIS)

Sasahara, Toshihiko

2008-01-01

Since the first reports of inter-granular stress corrosion crack (IGSCC) in boiling water reactor (BWR) pipe in the 1970s, nuclear power industry has focused considerable attention on service induced crack detection and sizing using ultrasonic examination. In recent years, phased array systems, those reconstruct high quality flaw images at real time are getting to apply for crack detection and sizing. But because the price of phased array systems are expensive for inspection vendors, field application of phased array systems are limited and reliable ultrasonic imaging systems with reasonable price are expected. This paper will discuss cost effective ultrasonic equipment with sectional image (B-scan) presentation as the simplified imaging system for assisting ultrasonic examination personnel. To develop the simplified B-scan imaging system, the frequency characteristics of IGSCC echoes and neighboring geometry echoes such as base-metal to weld interface and inner surface of a pipe are studied. The experimental study confirmed the reflectors have different frequency characteristics and 2MHz is suitable to visualize IGSCC and 5MHz and higher frequency are suitable to reconstruct geometry images. The other study is the amplifier selection for the imaging system. To reconstruct images of IGSCC and geometry echoes, the ultrasonic imaging instrument with linear amplifier has to adjust gain setting to the target. On the other hand, the ultrasonic imaging instrument with logarithmic amplifier can collect and display wider dynamic range on a screen and this wider dynamic range are effective to visualize IGSCC and geometry echoes on a B-scan presentation at a time. (author)

Multi-channel medical imaging system

Science.gov (United States)

Frangioni, John V

2013-12-31

A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remain in the subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may provide an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide used to capture images. The system may be configured for use in open surgical procedures by providing an operating area that is closed to ambient light. The systems described herein provide two or more diagnostic imaging channels for capture of multiple, concurrent diagnostic images and may be used where a visible light image may be usefully supplemented by two or more images that are independently marked for functional interest.

Limitations of the Current Microbial Identification System for Identification of Clinical Yeast Isolates

Science.gov (United States)

Kellogg, James A.; Bankert, David A.; Chaturvedi, Vishnu

1998-01-01

The ability of the rapid, computerized Microbial Identification System (MIS; Microbial ID, Inc.) to identify a variety of clinical isolates of yeast species was compared to the abilities of a combination of tests including the Yeast Biochemical Card (bioMerieux Vitek), determination of microscopic morphology on cornmeal agar with Tween 80, and when necessary, conventional biochemical tests and/or the API 20C Aux system (bioMerieux Vitek) to identify the same yeast isolates. The MIS chromatographically analyzes cellular fatty acids and compares the results with the fatty acid profiles in its database. Yeast isolates were subcultured onto Sabouraud dextrose agar and were incubated at 28°C for 24 h. The resulting colonies were saponified, methylated, extracted, and chromatographically analyzed (by version 3.8 of the MIS YSTCLN database) according to the manufacturer’s instructions. Of 477 isolates of 23 species tested, 448 (94%) were given species names by the MIS and 29 (6%) were unidentified (specified as “no match” by the MIS). Of the 448 isolates given names by the MIS, only 335 (75%) of the identifications were correct to the species level. While the MIS correctly identified only 102 (82%) of 124 isolates of Candida glabrata, the predictive value of an MIS identification of unknown isolates as C. glabrata was 100% (102 of 102) because no isolates of other species were misidentified as C. glabrata. In contrast, while the MIS correctly identified 100% (15 of 15) of the isolates of Saccharomyces cerevisiae, the predictive value of an MIS identification of unknown isolates as S. cerevisiae was only 47% (15 of 32), because 17 isolates of C. glabrata were misidentified as S. cerevisiae. The low predictive values for accuracy associated with MIS identifications for most of the remaining yeast species indicate that the procedure and/or database for the system need to be improved. PMID:9574676

A discrimination model in waste plastics sorting using NIR hyperspectral imaging system.

Science.gov (United States)

Zheng, Yan; Bai, Jiarui; Xu, Jingna; Li, Xiayang; Zhang, Yimin

2018-02-01

Classification of plastics is important in the recycling industry. A plastic identification model in the near infrared spectroscopy wavelength range 1000-2500 nm is proposed for the characterization and sorting of waste plastics using acrylonitrile butadiene styrene (ABS), polystyrene (PS), polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The model is built by the feature wavelengths of standard samples applying the principle component analysis (PCA), and the accuracy, property and cross-validation of the model were analyzed. The model just contains a simple equation, center of mass coordinates, and radial distance, with which it is easy to develop classification and sorting software. A hyperspectral imaging system (HIS) with the identification model verified its practical application by using the unknown plastics. Results showed that the identification accuracy of unknown samples is 100%. All results suggested that the discrimination model was potential to an on-line characterization and sorting platform of waste plastics based on HIS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of System Parameters by the Random Decrement Technique

DEFF Research Database (Denmark)

Brincker, Rune; Kirkegaard, Poul Henning; Rytter, Anders

-Walker equations and finally least square fitting of the theoretical correlation function. The results are compared to the results of fitting an Auto Regressive Moving Average(ARMA) model directly to the system output. All investigations are performed on the simulated output from a single degree-off-freedom system......The aim of this paper is to investigate and illustrate the possibilities of using correlation functions estimated by the Random Decrement Technique as a basis for parameter identification. A two-stage system identification method is used: first the correlation functions are estimated by the Random...... Decrement technique and then the system parameters are identified from the correlation function estimates. Three different techniques are used in the parameters identification process: a simple non-paramatic method, estimation of an Auto Regressive(AR) model by solving an overdetermined set of Yule...

Identification of time-varying nonlinear systems using differential evolution algorithm

DEFF Research Database (Denmark)

Perisic, Nevena; Green, Peter L; Worden, Keith

2013-01-01

(DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...

Efficient Filtering of Noisy Fingerprint Images

Directory of Open Access Journals (Sweden)

Maria Liliana Costin

2016-01-01

Full Text Available Fingerprint identification is an important field in the wide domain of biometrics with many applications, in different areas such: judicial, mobile phones, access systems, airports. There are many elaborated algorithms for fingerprint identification, but none of them can guarantee that the results of identification are always 100 % accurate. A first step in a fingerprint image analysing process consists in the pre-processing or filtering. If the result after this step is not by a good quality the upcoming identification process can fail. A major difficulty can appear in case of fingerprint identification if the images that should be identified from a fingerprint image database are noisy with different type of noise. The objectives of the paper are: the successful completion of the noisy digital image filtering, a novel more robust algorithm of identifying the best filtering algorithm and the classification and ranking of the images. The choice about the best filtered images of a set of 9 algorithms is made with a dual method of fuzzy and aggregation model. We are proposing through this paper a set of 9 filters with different novelty designed for processing the digital images using the following methods: quartiles, medians, average, thresholds and histogram equalization, applied all over the image or locally on small areas. Finally the statistics reveal the classification and ranking of the best algorithms.

Image quality of digital mammography images produced using wet and dry laser imaging systems

International Nuclear Information System (INIS)

Al Khalifah, K.; Brindhaban, A.; AlArfaj, R.; Jassim, O.

2006-01-01

Introduction: A study was carried out to compare the quality of digital mammographic images printed or processed by a wet laser imaging system and a dedicated mammographic dry laser imaging system. Material and methods: Digital images of a tissue equivalent breast phantom were obtained using a GE Senographe 2000D digital mammography system and different target/filter combinations of the X-ray tube. These images were printed on films using the Fuji FL-IM D wet laser imaging system and the Kodak DryView 8600 dry laser imaging system. The quality of images was assessed in terms of detectability of microcalcifications and simulated tumour masses by five radiologists. In addition, the contrast index and speed index of the two systems were measured using the step wedge in the phantom. The unpaired, unequal variance t-test was used to test any statistically significant differences. Results: There were no significant (p < 0.05) differences between the images printed using the two systems in terms of microcalcification and tumour mass detectability. The wet system resulted in slightly higher contrast index while the dry system showed significantly higher speed index. Conclusion: Both wet and dry laser imaging systems can produce mammography images of good quality on which 0.2 mm microcalcifications and 2 mm tumour masses can be detected. Dry systems are preferable due to the absence of wet chemical processing and solid or liquid chemical waste. The wet laser imaging systems, however, still represent a useful alternative to dry laser imaging systems for mammography studies

Towards the automated identification of Chrysomya blow flies from wing images.

Science.gov (United States)

Macleod, N; Hall, M J R; Wardhana, A H

2018-04-15

The Old World screwworm fly (OWSF), Chrysomya bezziana (Diptera: Calliphoridae), is an important agent of traumatic myiasis and, as such, a major human and animal health problem. In the implementation of OWSF control operations, it is important to determine the geographical origins of such disease-causing species in order to establish whether they derive from endemic or invading populations. Gross morphological and molecular studies have demonstrated the existence of two distinct lineages of this species, one African and the other Asian. Wing morphometry is known to be of substantial assistance in identifying the geographical origin of individuals because it provides diagnostic markers that complement molecular diagnostics. However, placement of the landmarks used in traditional geometric morphometric analysis can be time-consuming and subject to error caused by operator subjectivity. Here we report results of an image-based approach to geometric morphometric analysis for delivering wing-based identifications. Our results indicate that this approach can produce identifications that are practically indistinguishable from more traditional landmark-based results. In addition, we demonstrate that the direct analysis of digital wing images can be used to discriminate between three Chrysomya species of veterinary and forensic importance and between C. bezziana genders. © 2018 The Trustees of the Natural History Museum, London. Medical and Veterinary Entomology © 2018 Royal Entomological Society.

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

Science.gov (United States)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

System Identification of Mistuned Bladed Disks from Traveling Wave Response Measurements

Science.gov (United States)

Feiner, D. M.; Griffin, J. H.; Jones, K. W.; Kenyon, J. A.; Mehmed, O.; Kurkov, A. P.

2003-01-01

A new approach to modal analysis is presented. By applying this technique to bladed disk system identification methods, one can determine the mistuning in a rotor based on its response to a traveling wave excitation. This allows system identification to be performed under rotating conditions, and thus expands the applicability of existing mistuning identification techniques from integrally bladed rotors to conventional bladed disks.

Optical Verification Laboratory Demonstration System for High Security Identification Cards

Science.gov (United States)

Javidi, Bahram

1997-01-01

Document fraud including unauthorized duplication of identification cards and credit cards is a serious problem facing the government, banks, businesses, and consumers. In addition, counterfeit products such as computer chips, and compact discs, are arriving on our shores in great numbers. With the rapid advances in computers, CCD technology, image processing hardware and software, printers, scanners, and copiers, it is becoming increasingly easy to reproduce pictures, logos, symbols, paper currency, or patterns. These problems have stimulated an interest in research, development and publications in security technology. Some ID cards, credit cards and passports currently use holograms as a security measure to thwart copying. The holograms are inspected by the human eye. In theory, the hologram cannot be reproduced by an unauthorized person using commercially-available optical components; in practice, however, technology has advanced to the point where the holographic image can be acquired from a credit card-photographed or captured with by a CCD camera-and a new hologram synthesized using commercially-available optical components or hologram-producing equipment. Therefore, a pattern that can be read by a conventional light source and a CCD camera can be reproduced. An optical security and anti-copying device that provides significant security improvements over existing security technology was demonstrated. The system can be applied for security verification of credit cards, passports, and other IDs so that they cannot easily be reproduced. We have used a new scheme of complex phase/amplitude patterns that cannot be seen and cannot be copied by an intensity-sensitive detector such as a CCD camera. A random phase mask is bonded to a primary identification pattern which could also be phase encoded. The pattern could be a fingerprint, a picture of a face, or a signature. The proposed optical processing device is designed to identify both the random phase mask and the

Script Identification from Printed Indian Document Images and Performance Evaluation Using Different Classifiers

Directory of Open Access Journals (Sweden)

Sk Md Obaidullah

2014-01-01

multiscript country like India. In this paper the real life problem of printed script identification from official Indian document images is considered and performances of different well-known classifiers are evaluated. Two important evaluating parameters, namely, AAR (average accuracy rate and MBT (model building time, are computed for this performance analysis. Experiment was carried out on 459 printed document images with 5-fold cross-validation. Simple Logistic model shows highest AAR of 98.9% among all. BayesNet and Random Forest model have average accuracy rate of 96.7% and 98.2% correspondingly with lowest MBT of 0.09 s.

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

Science.gov (United States)

Laura, Jason; Rodriguez, Kelvin; Paquette, Adam C.; Dunn, Evin

2018-01-01

In this work we describe the AutoCNet library, written in Python, to support the application of computer vision techniques for n-image correspondence identification in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

International Nuclear Information System (INIS)

Xia, Bing; Zhao, Xin; Callafon, Raymond de; Garnier, Hugues; Nguyen, Truong; Mi, Chris

2016-01-01

Highlights: • Continuous-time system identification is applied in Lithium-ion battery modeling. • Continuous-time and discrete-time identification methods are compared in detail. • The instrumental variable method is employed to further improve the estimation. • Simulations and experiments validate the advantages of continuous-time methods. - Abstract: The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. However, in real applications, there is a fundamental limitation of the discrete-time methods in dealing with sensitivity when the system is stiff and the storage resolutions are limited. To overcome this problem, this paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to disturbances. A case of a 2"n"d-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. In addition, the estimation by the conventional continuous-time least squares method is further improved in the case of noisy output measurement by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the advantages of the continuous-time system identification methods in battery applications.

The BESIII muon identification system

International Nuclear Information System (INIS)

Zhang Jiawen; Qian Sen; Chen Jin; Du Zhizhen; Han Jifeng; Li Rubo; Liu Jichen; Liang Hao; Mao, Yajun; Ma Liehua; Wang Yifang; Xie Yigang; Xie Yuguang; Zhang Qingmin; Zhao Jianbing; Zhao, T.; Zhou, Yongzhao

2010-01-01

The muon identification system of BESIII experiment at the IHEP is described. The muon counter (MUC) is composed of resistive plate chambers (RPCs) working in self-quenching streamer mode with the gas mixture Ar/C 2 F 4 H 2 /C 4 H 10 =50/42/8. The design, the construction, the mass production and the quality control result of the detectors are described in detail. The paper also presents the performance of the bare RPCs and the superlayer modules with cosmic rays. Finally, the subsystems of MUC, including the RPC superlayer modules, the gas systems, the HV and LV system and the readout electronic system, are also presented.

Spectroscopy for identification of plasma sources for lithography and water window imaging

International Nuclear Information System (INIS)

O'Sullivan, Gerry; Dunne, Padraig; Liu, Luning; Lokasani, Ragava; Long, Elaine; O'Reilly, Fergal; Sheridan, Paul; Sokell, Emma; Wu, Tao; Higashiguchi, Takeshi; Li, Bowen; Ohashi, Hayato; Suzuki, Chihiro

2015-01-01

The identification of sources for applications that include nanolithography, surface patterning and high resolution imaging is the focus of a considerable activity in the extreme ultraviolet (EUV) or soft x-ray (SXR) spectral regions. We report on the result of a study of the spectra from laser produced plasmas of a number of medium and high Z metals undertaken in order to identify potential sources for use with available multilayer mirrors. The main focus was the study of unresolved transition arrays emitted from ions with 3d, 4d and 4f valence subshells that emit strongly in the water window (2.34-4.38 nm).and that could be used for biological imaging or cell tomography. (paper)

Improved Interactive Medical-Imaging System

Science.gov (United States)

Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

2003-01-01

An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

Automatic measurement of images on astrometric plates

Science.gov (United States)

Ortiz Gil, A.; Lopez Garcia, A.; Martinez Gonzalez, J. M.; Yershov, V.

1994-04-01

We present some results on the process of automatic detection and measurement of objects in overlapped fields of astrometric plates. The main steps of our algorithm are the following: determination of the Scale and Tilt between charge coupled devices (CCD) and microscope coordinate systems and estimation of signal-to-noise ratio in each field;--image identification and improvement of its position and size;--image final centering;--image selection and storage. Several parameters allow the use of variable criteria for image identification, characterization and selection. Problems related with faint images and crowded fields will be approached by special techniques (morphological filters, histogram properties and fitting models).

Near-infrared imaging spectroscopy for counterfeit drug detection

Science.gov (United States)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

Televison assessment and identification system for the plutonium protection system

International Nuclear Information System (INIS)

Greenwoll, D.A.

1979-02-01

This report covers the selection, description, and use of the components comprising the Television Assessment and Identification System in the Hanford Plutonium Protection System. This work was sponsored by the Department of Energy/Office of Safeguards and Security (DOE/OSS) as part of the overall Sandia Fixed Facility Physical Protection Program

Los Alamos Scientific Laboratory electronic vehicle identification system

International Nuclear Information System (INIS)

Landt, J.A.; Bobbett, R.E.; Koelle, A.R.; Salazar, P.H.

1980-01-01

A three-digit electronic identification system is described. Digits may be decimal (1000 combinations) or hexidecimal (8192 combinations). Battery-powered transponders are interrogated with a lower-power (1 W) radio signal. Line-of-sight interrogations up to 33 m (100 ft) are possible. Successful interrogations up to 7 m (20 ft) are possible for concealed transponders (that is, in the engine compartment). Vehicles moving at high rates of speed can be interrogated. This system provides data in a computer-compatible RS232 format. The system can be used for other applications with little or no modification. A similar system is in present use for identification and temperature monitoring of livestock. No unforeseen problems exist for expanding the coding scheme to identify larger numbers of objects

Development of a digital image correlation procedure adapted for kinematic measurements in polycrystals: application to the identification of crystal plasticity laws parameters

International Nuclear Information System (INIS)

Guery, Adrien

2014-01-01

A digital image correlation procedure adapted to kinematic measurements in polycrystals has been developed in this work to identify parameters of crystal plasticity laws. 2D kinematic measurements are performed on the surface of 316LN austenitic steel polycrystals from a sequence of images acquired using a Scanning Electron Microscope (SEM) during in-situ tensile tests for various mean grain sizes. To enable digital image correlation, a speckle adapted to the microscopic scale is deposited onto the specimen surface by a microlithography process. Spatial distortions resulting from both patterning and SEM imaging techniques are quantified. The knowledge of the microstructure at the surface by electron backscattered diffraction allows for kinematic measurements to be performed using an unstructured finite element mesh taking as support the grain or twin boundaries. This same mesh is then used for the simulation of each tensile test on the experimental microstructure with the measured nodal displacements prescribed as boundary conditions with their time evolution. Two local crystal plasticity laws are considered to simulate the observed strain heterogeneities, namely, the Meric-Cailletaud model and the DD-CFC law developed at EDF R and D. Comparisons between measurements and simulations are performed in terms of displacements, strains but also activated slip systems. Last, an inverse identification method is proposed for the identification of the sought constitutive parameters based on both the local displacement fields and the material homogenized behavior. The parameters associated with isotropic hardening of Meric-Cailletaud law are thus identified for various mean grain sizes. It is also shown that some of the interaction parameters of slip systems can be estimated. (author)

Estimation of identification limit for a small-type OSL dosimeter on the medical images by measurement of X-ray spectra

OpenAIRE

Takegami, Kazuki ; Hayashi, Hiroaki; Okino, Hiroki; Kimoto, Natsumi ; Maehata, Itsumi ; Kanazawa, Yuki ; Okazaki, Tohru ; Hashizume, Takuya ; Kobayashi, Ikuo 

2016-01-01

Our aim in this study is to derive an identification limit on a dosimeter for not disturbing a medical image when patients wear a small-type optically stimulated luminescence (OSL) dosimeter on their bodies during X-ray diagnostic imaging. For evaluation of the detection limit based on an analysis of X-ray spectra, we propose a new quantitative identification method. We performed experiments for which we used diagnostic X-ray equipment, a soft-tissue-equivalent phantom (1–20 cm), and a CdTe X...

Complete functional characterization of sensory neurons by system identification.

Science.gov (United States)

Wu, Michael C-K; David, Stephen V; Gallant, Jack L

2006-01-01

System identification is a growing approach to sensory neurophysiology that facilitates the development of quantitative functional models of sensory processing. This approach provides a clear set of guidelines for combining experimental data with other knowledge about sensory function to obtain a description that optimally predicts the way that neurons process sensory information. This prediction paradigm provides an objective method for evaluating and comparing computational models. In this chapter we review many of the system identification algorithms that have been used in sensory neurophysiology, and we show how they can be viewed as variants of a single statistical inference problem. We then review many of the practical issues that arise when applying these methods to neurophysiological experiments: stimulus selection, behavioral control, model visualization, and validation. Finally we discuss several problems to which system identification has been applied recently, including one important long-term goal of sensory neuroscience: developing models of sensory systems that accurately predict neuronal responses under completely natural conditions.

Subspace System Identification of the Kalman Filter

Directory of Open Access Journals (Sweden)

David Di Ruscio

2003-07-01

Full Text Available Some proofs concerning a subspace identification algorithm are presented. It is proved that the Kalman filter gain and the noise innovations process can be identified directly from known input and output data without explicitly solving the Riccati equation. Furthermore, it is in general and for colored inputs, proved that the subspace identification of the states only is possible if the deterministic part of the system is known or identified beforehand. However, if the inputs are white, then, it is proved that the states can be identified directly. Some alternative projection matrices which can be used to compute the extended observability matrix directly from the data are presented. Furthermore, an efficient method for computing the deterministic part of the system is presented. The closed loop subspace identification problem is also addressed and it is shown that this problem is solved and unbiased estimates are obtained by simply including a filter in the feedback. Furthermore, an algorithm for consistent closed loop subspace estimation is presented. This algorithm is using the controller parameters in order to overcome the bias problem.

a five year review of api20e bacteria identification system's

African Journals Online (AJOL)

The API20E system (API; bioMérieux, France) is a plastic strip with microtubes containing dehydrated substrates, originally designed for the identification of Enterobacteriaceae so that identification of fermenters with the system would be straightforward. The API20E system was extended to include non- fermenters by the ...

MAC, A System for Automatically IPR Identification, Collection and Distribution

Science.gov (United States)

Serrão, Carlos

Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

The diagnostic value of adding dynamic scintigraphy to standard delayed planar imaging for sentinel node identification in melanoma patients

International Nuclear Information System (INIS)

Nielsen, Kristina Rue; Nielsen, Michael B.; Chakera, Annette H.; Hesse, Birger; Oturai, Peter S.; Scolyer, Richard A.; Stretch, Jonathan F.; Thompson, John F.; Uren, Roger F.

2011-01-01

The aim of this study was to compare early dynamic imaging combined with delayed static imaging and single photon emission computed tomography (SPECT)/CT with delayed, planar, static imaging alone for sentinel node (SN) identification in melanoma patients. Three hundred and seven consecutive melanoma patients referred for SN biopsy (SNB) were examined using combined imaging. Secondary interpretation of only the delayed static images was subsequently performed. In 220 patients (72%), complete surgical and pathological information relating to the SNB was available. The number of SNs identified and number of patients with positive SNs were compared between the two interpretations of the imaging studies and, when available, related to pathology data. A slightly higher number of SNs (mean 0.12/patient) was identified when interpreting only delayed static images compared to combined imaging. In a direct patient-to-patient comparison, the number of SN(s) identified on the combined vs static images only showed moderate agreement (kappa value 0.56). In 38 patients (17%), positive SNs were identified by the combined procedure compared to 35 (16%) by static imaging only. Thus by static imaging only, tumour-positive SNs were not identified in 3 of 38 patients (8%). For SN identification in melanoma patients, dynamic imaging combined with delayed static imaging and SPECT/CT is superior to delayed static imaging only because the latter is more likely to fail to identify SNs containing metastases. (orig.)

Improving substructure identification accuracy of shear structures using virtual control system

Science.gov (United States)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

System identification and structural health monitoring of bridge structures

OpenAIRE

Islami, Kleidi

2013-01-01

This research study addresses two issues for the identification of structural characteristics of civil infrastructure systems. The first one is related to the problem of dynamic system identification, by means of experimental and operational modal analysis, applied to a large variety of bridge structures. Based on time and frequency domain techniques and mainly with output-only acceleration, velocity or strain data, modal parameters have been estimated for suspension bridges, masonry arch bri...

Research of Uncertainty Reasoning in Pineapple Disease Identification System

Science.gov (United States)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

System identification using Nuclear Norm & Tabu Search optimization

Science.gov (United States)

Ahmed, Asif A.; Schoen, Marco P.; Bosworth, Ken W.

2018-01-01

In recent years, subspace System Identification (SI) algorithms have seen increased research, stemming from advanced minimization methods being applied to the Nuclear Norm (NN) approach in system identification. These minimization algorithms are based on hard computing methodologies. To the authors’ knowledge, as of now, there has been no work reported that utilizes soft computing algorithms to address the minimization problem within the nuclear norm SI framework. A linear, time-invariant, discrete time system is used in this work as the basic model for characterizing a dynamical system to be identified. The main objective is to extract a mathematical model from collected experimental input-output data. Hankel matrices are constructed from experimental data, and the extended observability matrix is employed to define an estimated output of the system. This estimated output and the actual - measured - output are utilized to construct a minimization problem. An embedded rank measure assures minimum state realization outcomes. Current NN-SI algorithms employ hard computing algorithms for minimization. In this work, we propose a simple Tabu Search (TS) algorithm for minimization. TS algorithm based SI is compared with the iterative Alternating Direction Method of Multipliers (ADMM) line search optimization based NN-SI. For comparison, several different benchmark system identification problems are solved by both approaches. Results show improved performance of the proposed SI-TS algorithm compared to the NN-SI ADMM algorithm.

Hypertensive retinopathy identification through retinal fundus image using backpropagation neural network

Science.gov (United States)

Syahputra, M. F.; Amalia, C.; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Nurdin; Andayani, U.

2018-03-01

Hypertension or high blood pressure can cause damage of blood vessels in the retina of eye called hypertensive retinopathy (HR). In the event Hypertension, it will cause swelling blood vessels and a decrese in retina performance. To detect HR in patients body, it is usually performed through physical examination of opthalmoscope which is still conducted manually by an ophthalmologist. Certainly, in such a manual manner, takes a ong time for a doctor to detetct HR on aa patient based on retina fundus iamge. To overcome ths problem, a method is needed to identify the image of retinal fundus automatically. In this research, backpropagation neural network was used as a method for retinal fundus identification. The steps performed prior to identification were pre-processing (green channel, contrast limited adapative histogram qualization (CLAHE), morphological close, background exclusion, thresholding and connected component analysis), feature extraction using zoning. The results show that the proposed method is able to identify retinal fundus with an accuracy of 95% with maximum epoch of 1500.

Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)

OpenAIRE

Goeau, Herve; Bonnet, Pierre; Joly, Alexis

2017-01-01

International audience; The 2017-th edition of the LifeCLEF plant identification challenge is an important milestone towards automated plant identification systems working at the scale of continental floras with 10.000 plant species living mainly in Europe and North America illustrated by a total of 1.1M images. Nowadays, such ambitious systems are enabled thanks to the conjunction of the dazzling recent progress in image classification with deep learning and several outstanding international...

Physics-based mathematical models for quantum devices via experimental system identification

Energy Technology Data Exchange (ETDEWEB)

Schirmer, S G; Oi, D K L; Devitt, S J [Department of Applied Maths and Theoretical Physics, University of Cambridge, Wilberforce Rd, Cambridge, CB3 0WA (United Kingdom); SUPA, Department of Physics, University of Strathclyde, Glasgow G4 0NG (United Kingdom); National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430 (Japan)], E-mail: sgs29@cam.ac.uk

2008-03-15

We consider the task of intrinsic control system identification for quantum devices. The problem of experimental determination of subspace confinement is considered, and simple general strategies for full Hamiltonian identification and decoherence characterization of a controlled two-level system are presented.

Time-Efficient Cloning Attacks Identification in Large-Scale RFID Systems

Directory of Open Access Journals (Sweden)

Ju-min Zhao

2017-01-01

Full Text Available Radio Frequency Identification (RFID is an emerging technology for electronic labeling of objects for the purpose of automatically identifying, categorizing, locating, and tracking the objects. But in their current form RFID systems are susceptible to cloning attacks that seriously threaten RFID applications but are hard to prevent. Existing protocols aimed at detecting whether there are cloning attacks in single-reader RFID systems. In this paper, we investigate the cloning attacks identification in the multireader scenario and first propose a time-efficient protocol, called the time-efficient Cloning Attacks Identification Protocol (CAIP to identify all cloned tags in multireaders RFID systems. We evaluate the performance of CAIP through extensive simulations. The results show that CAIP can identify all the cloned tags in large-scale RFID systems fairly fast with required accuracy.

Poka Yoke system based on image analysis and object recognition

Science.gov (United States)

Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

2015-11-01

Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

The DIRC Particle Identification System for the BaBar Experiment

Energy Technology Data Exchange (ETDEWEB)

Adam, I

2004-06-30

A new type of ring-imaging Cherenkov detector is being used for hadronic particle identification in the BABAR experiment at the SLAC B Factory (PEP-II). This detector is called DIRC, an acronym for Detection of Internally Reflected Cherenkov (Light). This paper will discuss the construction, operation and performance of the BABAR DIRC in detail.

OSPACS: Ultrasound image management system

Directory of Open Access Journals (Sweden)

Bessant Conrad

2008-06-01

Full Text Available Abstract Background Ultrasound scanning uses the medical imaging format, DICOM, for electronically storing the images and data associated with a particular scan. Large health care facilities typically use a picture archiving and communication system (PACS for storing and retrieving such images. However, these systems are usually not suitable for managing large collections of anonymized ultrasound images gathered during a clinical screening trial. Results We have developed a system enabling the accurate archiving and management of ultrasound images gathered during a clinical screening trial. It is based upon a Windows application utilizing an open-source DICOM image viewer and a relational database. The system automates the bulk import of DICOM files from removable media by cross-validating the patient information against an external database, anonymizing the data as well as the image, and then storing the contents of the file as a field in a database record. These image records may then be retrieved from the database and presented in a tree-view control so that the user can select particular images for display in a DICOM viewer or export them to external media. Conclusion This system provides error-free automation of ultrasound image archiving and management, suitable for use in a clinical trial. An open-source project has been established to promote continued development of the system.

A Portable, Air-Jet-Actuator-Based Device for System Identification

Science.gov (United States)

Staats, Wayne; Belden, Jesse; Mazumdar, Anirban; Hunter, Ian

2010-11-01

System identification (ID) of human and robotic limbs could help in diagnosis of ailments and aid in optimization of control parameters and future redesigns. We present a self-contained actuator, which uses the Coanda effect to rapidly switch the direction of a high speed air jet to create a binary stochastic force input to a limb for system ID. The design of the actuator is approached with the goal of creating a portable device, which could deployed on robot or human limbs for in situ identification. The viability of the device is demonstrated by performing stochastic system ID on an underdamped elastic beam system with fixed inertia and stiffness, and variable damping. The non-parametric impulse response yielded from the stochastic system ID is modeled as a second order system, and the resultant parameters are found to be in excellent agreement with those found using more traditional system ID techniques. The current design could be further miniaturized and developed as a portable, wireless, on-site multi-axis system identification system for less intrusive and more widespread use.

New image-stabilizing system

Science.gov (United States)

Zhao, Yuejin

1996-06-01

In this paper, a new method for image stabilization with a three-axis image- stabilizing reflecting prism assembly is presented, and the principle of image stabilization in this prism assembly, formulae for image stabilization and working formulae with an approximation up to the third power are given in detail. In this image-stabilizing system, a single chip microcomputer is used to calculate value of compensating angles and thus to control the prism assembly. Two gyroscopes act as sensors from which information of angular perturbation is obtained, three stepping motors drive the prism assembly to compensate for the movement of image produced by angular perturbation. The image-stabilizing device so established is a multifold system which involves optics, mechanics, electronics and computer.

Study on the knowledge base system for the identification of typical target

International Nuclear Information System (INIS)

Qin Kai; Zhao Yingjun

2008-01-01

Based on the research on target knowledge base, target database, texture analysis, shape analysis, this paper proposed a new knowledge based method for typical target identification from remote sensing image. By extracting the texture characters and shape characters, joining with spatial analysis in GIS, reasoning according to the prior knowledge in the knowledge base, this method can identify and ex- tract typical target from remote sensing images. (authors)

21 CFR 880.6300 - Implantable radiofrequency transponder system for patient identification and health information.

Science.gov (United States)

2010-04-01

... patient identification and health information. 880.6300 Section 880.6300 Food and Drugs FOOD AND DRUG... radiofrequency transponder system for patient identification and health information. (a) Identification. An implantable radiofrequency transponder system for patient identification and health information is a device...

System identification with information theoretic criteria

NARCIS (Netherlands)

A.A. Stoorvogel; J.H. van Schuppen (Jan)

1995-01-01

textabstractAttention is focused in this paper on the approximation problem of system identification with information theoretic criteria. For a class of problems it is shown that the criterion of mutual information rate is identical to the criterion of exponential-of-quadratic cost and to

Modeling emotional content of music using system identification.

Science.gov (United States)

Korhonen, Mark D; Clausi, David A; Jernigan, M Ed

2006-06-01

Research was conducted to develop a methodology to model the emotional content of music as a function of time and musical features. Emotion is quantified using the dimensions valence and arousal, and system-identification techniques are used to create the models. Results demonstrate that system identification provides a means to generalize the emotional content for a genre of music. The average R2 statistic of a valid linear model structure is 21.9% for valence and 78.4% for arousal. The proposed method of constructing models of emotional content generalizes previous time-series models and removes ambiguity from classifiers of emotion.

Improved Palmprint Identification System

Directory of Open Access Journals (Sweden)

Harshala C. Salave

2015-03-01

Full Text Available Abstract Generally private information is provided by using passwords or Personal Identification Numbers which is easy to implement but it is very easily stolen or forgotten or hack. In Biometrics for individuals identification uses human physiological which are constant throughout life like palm face DNA iris etc. or behavioral characteristicswhich is not constant in life like voice signature keystroke etc.. But mostly gain more attention to palmprint identification and is becoming more popular technique using for identification and promising alternatives to the traditional password or PIN based authentication techniques. In this paper propose palmprint identification using veins on the palm and fingers. Here use fusion of techniques such as Discrete Wavelet transformDWT Canny Edge Detector Gaussian Filter Principle Component AnalysisPCA.

System identification: a frequency domain approach

National Research Council Canada - National Science Library

Pintelon, R; Schoukens, J

2001-01-01

... in the Identification Process 17 1.4.1 Collect Information about the System 17 1.4.2 Select a Model Structure to Represent the System 17 1.4.3 Match the Selected Model Structure to the Measurements 19 1.4.4 Validate the Selected Model 19 1.4.5 Conclusion 19 A Statistical Approach to the Estimation Problem 1.5.1 Least Squares Estimation 20 1.5.2 Weighted Least Squar...

Health monitoring system for transmission shafts based on adaptive parameter identification

Science.gov (United States)

Souflas, I.; Pezouvanis, A.; Ebrahimi, K. M.

2018-05-01

A health monitoring system for a transmission shaft is proposed. The solution is based on the real-time identification of the physical characteristics of the transmission shaft i.e. stiffness and damping coefficients, by using a physical oriented model and linear recursive identification. The efficacy of the suggested condition monitoring system is demonstrated on a prototype transient engine testing facility equipped with a transmission shaft capable of varying its physical properties. Simulation studies reveal that coupling shaft faults can be detected and isolated using the proposed condition monitoring system. Besides, the performance of various recursive identification algorithms is addressed. The results of this work recommend that the health status of engine dynamometer shafts can be monitored using a simple lumped-parameter shaft model and a linear recursive identification algorithm which makes the concept practically viable.

Army medical imaging system: ARMIS

International Nuclear Information System (INIS)

Siedband, M.P.; Kramp, D.C.

1987-01-01

Recent advances of stimulable phosphor screens, data cards using optical storage means, and new personal computers with image processing capability have made possible the design of economical filmless medical imaging systems. The addition of communication links means that remote interpretation of images is also possible. The Army Medical Imaging System uses stimulable phosphor screens, digital readout, a small computer, an optical digital data card device, and a DIN/PACS link. Up to 200 images can be stored in the computer hard disk for rapid recall and reading by the radiologist. The computer permits image processing, annotation, insertion of text, and control of the system. Each device contains an image storage RAM and communicates with the computer via the small computer systems interface. Data compression is used to reduce the required storage capacity and transmission times of the 1-mB images. The credit card-size optical data cards replace film and can store 12 or more images. The data cards can be read on an independent viewer. The research is supported by the U.S. Army Biomedical Research and Development Laboratory

Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

Science.gov (United States)

Fauziah; Wibowo, E. P.; Madenda, S.; Hustinawati

2018-03-01

Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of parameters tested, it appears that architecture provides the highest accuracy in one hundred hidden neural network. The architecture is used propagate the input value of the system implementation process into the user interface. The result of the identification of the type of the human movement has been clone to produce the highest acuracy of 98.5447%. The training process is done to get the best results.

Design of low noise imaging system

Science.gov (United States)

Hu, Bo; Chen, Xiaolai

2017-10-01

In order to meet the needs of engineering applications for low noise imaging system under the mode of global shutter, a complete imaging system is designed based on the SCMOS (Scientific CMOS) image sensor CIS2521F. The paper introduces hardware circuit and software system design. Based on the analysis of key indexes and technologies about the imaging system, the paper makes chips selection and decides SCMOS + FPGA+ DDRII+ Camera Link as processing architecture. Then it introduces the entire system workflow and power supply and distribution unit design. As for the software system, which consists of the SCMOS control module, image acquisition module, data cache control module and transmission control module, the paper designs in Verilog language and drives it to work properly based on Xilinx FPGA. The imaging experimental results show that the imaging system exhibits a 2560*2160 pixel resolution, has a maximum frame frequency of 50 fps. The imaging quality of the system satisfies the requirement of the index.

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

Directory of Open Access Journals (Sweden)

Feng Qin

Full Text Available Common leaf spot (caused by Pseudopeziza medicaginis, rust (caused by Uromyces striatus, Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana and Cercospora leaf spot (caused by Cercospora medicaginis are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis. After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection, disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features was the optimal model. For this SVM model, the

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

Science.gov (United States)

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the

HOC Based Blind Identification of Hydroturbine Shaft Volterra System

Directory of Open Access Journals (Sweden)

Bing Bai

2017-01-01

Full Text Available In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d., zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method with genetic algorithm (GA and constituted the hybrid genetic algorithm (HGA. Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system.

Artificial intelligence and medical imaging. Expert systems and image analysis

International Nuclear Information System (INIS)

Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

1987-01-01

This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

Highly integrated image sensors enable low-cost imaging systems

Science.gov (United States)

Gallagher, Paul K.; Lake, Don; Chalmers, David; Hurwitz, J. E. D.

1997-09-01

The highest barriers to wide scale implementation of vision systems have been cost. This is closely followed by the level of difficulty of putting a complete imaging system together. As anyone who has every been in the position of creating a vision system knows, the various bits and pieces supplied by the many vendors are not under any type of standardization control. In short, unless you are an expert in imaging, electrical interfacing, computers, digital signal processing, and high speed storage techniques, you will likely spend more money trying to do it yourself rather than to buy the exceedingly expensive systems available. Another alternative is making headway into the imaging market however. The growing investment in highly integrated CMOS based imagers is addressing both the cost and the system integration difficulties. This paper discusses the benefits gained from CMOS based imaging, and how these benefits are already being applied.

Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT

Directory of Open Access Journals (Sweden)

Niko Nevaranta

2015-07-01

Full Text Available A proper system identification method is of great importance in the process of acquiring an analytical model that adequately represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach for system diagnostics, the frequency domain identification techniques have primarily been considered for offline commissioning purposes. This paper addresses issues in the online frequency domain identification of a flexible two-mass mechanical system with varying dynamics, and a particular attention is paid to detect the changes in the system dynamics. An online identification method is presented that is based on a recursive Kalman filter configured to perform like a discrete Fourier transform (DFT at a selected set of frequencies. The experimental online identification results are compared with the corresponding values obtained from the offline-identified frequency responses. The results show an acceptable agreement and demonstrate the feasibility of the proposed identification method.

Fundamental limits for privacy-preserving biometric identification systems that support authentication

NARCIS (Netherlands)

Ignatenko, T.; Willems, F.M.J.

2015-01-01

In this paper we analyze two types of biometric identification systems with protected templates that also support authentication. In the first system two terminals observe biometric enrollment and identification sequences of a number of individuals. It is the goal of these terminals to form a common

28 CFR 20.36 - Participation in the Interstate Identification Index System.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Participation in the Interstate Identification Index System. 20.36 Section 20.36 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL JUSTICE... in the Interstate Identification Index System. (a) In order to acquire and retain direct access to...

2009 United States Automatic Identification System Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2009 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

2014 United States Automatic Identification System Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2014 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

2012 United States Automatic Identification System Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2012 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

2010 United States Automatic Identification System Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2010 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

2011 United States Automatic Identification System Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The 2011 United States Automatic Identification System Database contains vessel traffic data for planning purposes within the U.S. coastal waters. The database is...

Automated Identification of Fiducial Points on 3D Torso Images

Directory of Open Access Journals (Sweden)

Manas M. Kawale

2013-01-01

Full Text Available Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D coordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship.

Os acromiale: evaluation of markers for identification on sagittal and coronal oblique MR images

Energy Technology Data Exchange (ETDEWEB)

Uri, D.S. [University of Michigan, Dept. of Radiology, Ann Arbor, MI (United States)]|[Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia (United States); Kneeland, J.B. [Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia (United States); Herzog, R. [Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia (United States)

1997-01-01

An os acromiale is a developmental abnormality of ossification involving the anterior acromion which may contribute to impingement and rotator cuff disease. When axial MR sections do not include the acromioclavicular joint, the diagnosis of this often subtle abnormality will rest on its recognition on oblique coronal and sagittal images where it mimics the acromioclavicular joint. The identification of this anomaly is important as it frequently alters the type of surgical procedure utilized in symptomatic patients. We evaluate several imaging features which may be used to diagnose an os acromiale in these cases. (orig.). With 5 figs.

Os acromiale: evaluation of markers for identification on sagittal and coronal oblique MR images

International Nuclear Information System (INIS)

Uri, D.S.; Kneeland, J.B.; Herzog, R.

1997-01-01

An os acromiale is a developmental abnormality of ossification involving the anterior acromion which may contribute to impingement and rotator cuff disease. When axial MR sections do not include the acromioclavicular joint, the diagnosis of this often subtle abnormality will rest on its recognition on oblique coronal and sagittal images where it mimics the acromioclavicular joint. The identification of this anomaly is important as it frequently alters the type of surgical procedure utilized in symptomatic patients. We evaluate several imaging features which may be used to diagnose an os acromiale in these cases. (orig.). With 5 figs

RMB identification based on polarization parameters inversion imaging

Science.gov (United States)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

Social order is threatened by counterfeit money. Conventional anti-counterfeit technology is much too old to identify its authenticity or not. The intrinsic difference between genuine notes and counterfeit notes is its paper tissue. In this paper a new technology of detecting RMB is introduced, the polarization parameter indirect microscopic imaging technique. A conventional reflection microscopic system is used as the basic optical system, and inserting into it with polarization-modulation mechanics. The near-field structural characteristics can be delivered by optical wave and material coupling. According to coupling and conduction physics, calculate the changes of optical wave parameters, then get the curves of the intensity of the image. By analyzing near-field polarization parameters in nanoscale, finally calculate indirect polarization parameter imaging of the fiber of the paper tissue in order to identify its authenticity.

Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

Directory of Open Access Journals (Sweden)

Zongze Wu

2015-08-01

Full Text Available Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE criterion, which is optimal only when the measurement noise is Gaussian. However, this condition does not hold in most real-world environments. In this work, we use the minimum error entropy (MEE criterion, an alternative to the conventional MSE criterion, to develop the proportionate minimum error entropy (PMEE algorithm for sparse system identification, which may achieve much better performance than the MSE based methods especially in heavy-tailed non-Gaussian situations. Moreover, we analyze the convergence of the proposed algorithm and derive a sufficient condition that ensures the mean square convergence. Simulation results confirm the excellent performance of the new algorithm.

Nuclear power plant transient identification using a neuro-fuzzy inference system

International Nuclear Information System (INIS)

Mol, Antonio Carlos de Abreu; Oliveira, Mauro Vitor de; Santos, Isaac Jose Antonio Luchetti dos; Carvalho, Paulo Victor Rodrigues de; Grecco, Claudio Henrique dos Santos; Auguto, Silas Cordeiro

2005-01-01

Transient identification in Nuclear Power Plant (NPP) is often a very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in nuclear power plants. The basis for the identification of a change in the system is that different system faults and anomalies lead to different patterns of evolution of the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments, that represents a specific type of event. In this work, an approach for the identification of transients is presented, aiming at helping the operator to make a decision relative to the procedure to be followed in situations of accidents/transients at nuclear power plants. In this way, a diagnostic strategy based on hierarchical use artificial neural networks (ANN) for a first level transient diagnose. After the ANN has done a preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. In order to validate the method, a Nuclear Power Plant transient identification problem, comprising postulated accidents, is proposed. Noisy data was used to evaluate the method robustness. The results obtained reveal the ability of the method in dealing with dynamic identification of transients and its reliability degree. (author)

Imaging system

International Nuclear Information System (INIS)

Rushbrooke, J.G.; Ansorge, R.E.

1987-01-01

A moving object such as a container on a conveyor belt is imaged by an optical system onto a charge coupled device array in which the lines of the array are arranged perpendicular to the direction of motion of the object. The speed of movement of the object is sensed to generate electrical signals which are processed to provide shift signals enabling the shifting of data row to row in the array in synchronism with the movement of the container. The electrical charge associated with a given point on the array is transferred from one line to the other until it appears at the last line of the array, from which it is read out in known manner in conjunction with all other electrical charges associated with the row of charge coupled devices in the last line of the array. Due to the integrating effect achieved, the aperture of the imaging system can be much smaller than otherwise would be required, and/or the level of light illumination can be reduced. The imaging system can be applied to X-ray inspection devices, aerial surveillance or scanning of moving documents in copying processes. (author)

Practical Modeling and Comprehensive System Identification of a BLDC Motor

Directory of Open Access Journals (Sweden)

Changle Xiang

2015-01-01

Full Text Available The aim of this paper is to outline all the steps in a rigorous and simple procedure for system identification of BLDC motor. A practical mathematical model for identification is derived. Frequency domain identification techniques and time domain estimation method are combined to obtain the unknown parameters. The methods in time domain are founded on the least squares approximation method and a disturbance observer. Only the availability of experimental data for rotor speed and armature current are required for identification. The proposed identification method is systematically investigated, and the final identified model is validated by experimental results performed on a typical BLDC motor in UAV.

Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

Science.gov (United States)

Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

2018-03-01

Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

Handheld microwave bomb-detecting imaging system

Science.gov (United States)

Gorwara, Ashok; Molchanov, Pavlo

2017-05-01

Proposed novel imaging technique will provide all weather high-resolution imaging and recognition capability for RF/Microwave signals with good penetration through highly scattered media: fog, snow, dust, smoke, even foliage, camouflage, walls and ground. Image resolution in proposed imaging system is not limited by diffraction and will be determined by processor and sampling frequency. Proposed imaging system can simultaneously cover wide field of view, detect multiple targets and can be multi-frequency, multi-function. Directional antennas in imaging system can be close positioned and installed in cell phone size handheld device, on small aircraft or distributed around protected border or object. Non-scanning monopulse system allows dramatically decrease in transmitting power and at the same time provides increased imaging range by integrating 2-3 orders more signals than regular scanning imaging systems.

Fission gas bubble identification using MATLAB's image processing toolbox

Energy Technology Data Exchange (ETDEWEB)

Collette, R. [Colorado School of Mines, Nuclear Science and Engineering Program, 1500 Illinois St, Golden, CO 80401 (United States); King, J., E-mail: kingjc@mines.edu [Colorado School of Mines, Nuclear Science and Engineering Program, 1500 Illinois St, Golden, CO 80401 (United States); Keiser, D.; Miller, B.; Madden, J.; Schulthess, J. [Nuclear Fuels and Materials Division, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-6188 (United States)

2016-08-15

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

A system boundary identification method for life cycle assessment

DEFF Research Database (Denmark)

Li, Tao; Zhang, Hongchao; Liu, Zhichao

2014-01-01

, technical, geographical and temporal dimensions are presented to limit the boundaries of LCA. An algorithm is developed to identify an appropriate boundary by searching the process tree and evaluating the environmental impact contribution of each process while it is added into the studied system...... as processes are added. The two threshold rules and identification methods presented can be used to identify system boundary of LCA. The case study demonstrated that the methodology presented in this paper is an effective tool for the boundary identification....

LPV Identification of a Heat Distribution System

DEFF Research Database (Denmark)

Trangbæk, K; Bendtsen, Jan Dimon

2010-01-01

This paper deals with incremental system identification of district heating systems to improve control performance. As long as various parameters, e.g. valve settings, are kept fixed, the dynamics of district heating systems can be approximated well by linear models; however, the dynamics change ....... The approach is tested on a laboratory setup emulating a district heating system, where local controllers regulate pumps connected to a common supply. Experiments show that cross-couplings in the system can indeed be identified in closed-loop operation....

Expert system based radionuclide identification

International Nuclear Information System (INIS)

Aarnio, P.A.; Ala-Heikkil, J.J.; Hakulinen, T.T.; Nikkinen, M.T.

1998-01-01

An expert system coupled with the gamma spectrum analysis system SAMPO has been developed for automating the qualitative identification of radionuclides as well as for determining the quantitative parameters of the spectrum components. The program is written in C-language and runs in various environments ranging from PCs to UNIX workstations. The expert system utilizes a complete gamma library with over 2600 nuclides and 80,000 lines, and a rule base of about fifty criteria including energies, relative peak intensities, genesis modes, half lives, parent-daughter relationships, etc. The rule base is furthermore extensible by the user. This is not an original contribution but a somewhat updated version of papers and reports previously published elsewhere. (author)

Multispectral imaging for biometrics

Science.gov (United States)

Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

2005-03-01

Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

Acquiring and preprocessing leaf images for automated plant identification: understanding the tradeoff between effort and information gain

Directory of Open Access Journals (Sweden)

Michael Rzanny

2017-11-01

Full Text Available Abstract Background Automated species identification is a long term research subject. Contrary to flowers and fruits, leaves are available throughout most of the year. Offering margin and texture to characterize a species, they are the most studied organ for automated identification. Substantially matured machine learning techniques generate the need for more training data (aka leaf images. Researchers as well as enthusiasts miss guidance on how to acquire suitable training images in an efficient way. Methods In this paper, we systematically study nine image types and three preprocessing strategies. Image types vary in terms of in-situ image recording conditions: perspective, illumination, and background, while the preprocessing strategies compare non-preprocessed, cropped, and segmented images to each other. Per image type-preprocessing combination, we also quantify the manual effort required for their implementation. We extract image features using a convolutional neural network, classify species using the resulting feature vectors and discuss classification accuracy in relation to the required effort per combination. Results The most effective, non-destructive way to record herbaceous leaves is to take an image of the leaf’s top side. We yield the highest classification accuracy using destructive back light images, i.e., holding the plucked leaf against the sky for image acquisition. Cropping the image to the leaf’s boundary substantially improves accuracy, while precise segmentation yields similar accuracy at a substantially higher effort. The permanent use or disuse of a flash light has negligible effects. Imaging the typically stronger textured backside of a leaf does not result in higher accuracy, but notably increases the acquisition cost. Conclusions In conclusion, the way in which leaf images are acquired and preprocessed does have a substantial effect on the accuracy of the classifier trained on them. For the first time, this

System Identification for Integrated Aircraft Development and Flight Testing (l’Identification des systemes pour le developpement integre des aeronefs et les essais en vol)

Science.gov (United States)

1999-03-01

aerodynamics to affect load motions. The effects include a load trail angle in proportion to the drag specific force, and modification of the load pendulum...equations algorithm for flight data filtering architeture . and data consistency checking; and SCIDNT 8, an output architecture. error identification...accelerations at the seven sensor locations, identified system is proportional to the number When system identification is performed, as of flexible modes

Lorestan Bronze Plate Design Identification by Nondestructive Radiography Method and Image Processing by Means of Histogram Matching

International Nuclear Information System (INIS)

Yahaghi, E.; Movafeghi, A.; Ahmadi, S.; Rokrok, B.; Mohammadzadeh, N.; Rastkhah, N.

2013-01-01

Radiography is known as one of the oldest and most widely used nondestructive testing techniques, where it introduces the most appreciated technique by producing images which are acting as unique fingerprint records of samples of interest. Among the interesting applications of radiography are archaeological and art applications. In this research, radiography was implemented for identification of a damaged art-historical material. The sample was a brass plate belonging to Iran cultural heritage. The estimated age of the plate was about 3500 years. The plate was discovered in Lorestan province, where it is generally called L orestan bronze . The plate was damaged seriously due to serious corrosion environmental attacks, and recognition of the sample was considered as the major problem. The simple radiography method was quite helpful for the plate determination but the method suffered from some major drawbacks due to contrast and thickness measurements. The thickness measurement and corrosion/erosion evaluation were the vital components of the inspection. The image processing techniques and precise thickness measurement method were added to the digitized radiographs. For the digital image processing, a histogram matching algorithm and an edge detection method were used. After all, the resulted image showed an enhanced quality image of the original traces of the hammered design. The results showed that a good experimental setup of radiography along with the image processing technique can give a high quality radiographic image which is able to be used effectively for the identification of art antiques. The human evaluation results also confirmed the ability of the proposed method with a high degree of certainty.

Effect of reconstruction algorithm on image quality and identification of ground-glass opacities and partly solid nodules on low-dose thin-section CT: Experimental study using chest phantom

International Nuclear Information System (INIS)

Koyama, Hisanobu; Ohno, Yoshiharu; Kono, Atsushi A.; Kusaka, Akiko; Konishi, Minoru; Yoshii, Masaru; Sugimura, Kazuro

2010-01-01

Purpose: The purpose of this study was to assess the influence of reconstruction algorithm on identification and image quality of ground-glass opacities (GGOs) and partly solid nodules on low-dose thin-section CT. Materials and methods: A chest CT phantom including simulated GGOs and partly solid nodules was scanned with five different tube currents and reconstructed by using standard (A) and newly developed (B) high-resolution reconstruction algorithms, followed by visually assessment of identification and image quality of GGOs and partly solid nodules by two chest radiologists. Inter-observer agreement, ROC analysis and ANOVA were performed to compare identification and image quality of each data set with those of the standard reference. The standard reference used 120 mA s in conjunction with reconstruction algorithm A. Results: Kappa values (κ) of overall identification and image qualities were substantial or almost perfect (0.60 < κ). Assessment of identification showed that area under the curve of 25 mA reconstructed with reconstruction algorithm A was significantly lower than that of standard reference (p < 0.05), while assessment of image quality indicated that 50 mA s reconstructed with reconstruction algorithm A and 25 mA s reconstructed with both reconstruction algorithms were significantly lower than standard reference (p < 0.05). Conclusion: Reconstruction algorithm may be an important factor for identification and image quality of ground-glass opacities and partly solid nodules on low-dose CT examination.

Experiment design for identification of structured linear systems

NARCIS (Netherlands)

Potters, M.G.

2016-01-01

Experiment Design for system identification involves the design of an optimal input signal with the purpose of accurately estimating unknown parameters in a system. Specifically, in the Least-Costly Experiment Design (LCED) framework, the optimal input signal results from an optimisation problem in

IDAPS (Image Data Automated Processing System) System Description

Science.gov (United States)

1988-06-24

This document describes the physical configuration and components used in the image processing system referred to as IDAPS (Image Data Automated ... Processing System). This system was developed by the Environmental Research Institute of Michigan (ERIM) for Eglin Air Force Base. The system is designed

Identification of apical vertebra for grading of idiopathic scoliosis using image processing.

Science.gov (United States)

Anitha, H; Prabhu, G K

2012-02-01

Scoliosis is a 3-D deformity of spinal column, characterized by both lateral curvature and vertebral rotation. The disease can be caused by congenital, developmental, or degenerative problems; but most cases of scoliosis actually have no known cause, and this is known as idiopathic scoliosis. Vertebral rotation has become increasingly prominent in the study of scoliosis and the most deformed vertebra is named as apical vertebra. Apical vertebral deformity demonstrates significance in both preoperative and postoperative assessment, providing better appreciation of the impact of bracing or surgical interventions. Precise measurement of apical vertebral rotation in terms of grading is most valuable for the determination of reference value in normal and pathological conditions for better understanding of scoliosis. Routine quantitative evaluation of vertebral rotation is difficult and error prone due to limitations of observer characteristic and specific imaging property. This paper proposes automatic identification of the apical vertebra and its parameter that depends on the objective criteria of measurement using active contour models. The proposed technique is more accurate and is a reliable measurement compared to manual and computer-assisted system.

Vortex Tube Modeling Using the System Identification Method

Energy Technology Data Exchange (ETDEWEB)

Han, Jaeyoung; Jeong, Jiwoong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Im, Seokyeon [Tongmyong Univ., Busan (Korea, Republic of)

2017-05-15

In this study, vortex tube system model is developed to predict the temperature of the hot and the cold sides. The vortex tube model is developed based on the system identification method, and the model utilized in this work to design the vortex tube is ARX type (Auto-Regressive with eXtra inputs). The derived polynomial model is validated against experimental data to verify the overall model accuracy. It is also shown that the derived model passes the stability test. It is confirmed that the derived model closely mimics the physical behavior of the vortex tube from both the static and dynamic numerical experiments by changing the angles of the low-temperature side throttle valve, clearly showing temperature separation. These results imply that the system identification based modeling can be a promising approach for the prediction of complex physical systems, including the vortex tube.

Imaging systems in nuclear medicine and image evaluation

International Nuclear Information System (INIS)

Beck, R.; Charleston, D.; Metz, C.; Tsui, B.

1981-01-01

A general computer code to simulate the imaging properties of existing and hypothetical imaging systems viewing realistic source distributions within non-uniform media. Such a code allows comparative evaluations of existing and hypothetical systems, and optimization of critical parameters of system design by maximizing the signal-to-noise ratio. To be most useful, such a code allows simulation of conventional scintillation scanners and cameras as well as single-photon and position tomographic systems

Analysis of image plane's Illumination in Image-forming System

International Nuclear Information System (INIS)

Duan Lihua; Zeng Yan'an; Zhang Nanyangsheng; Wang Zhiguo; Yin Shiliang

2011-01-01

In the detection of optical radiation, the detecting accuracy is affected by optic power distribution of the detector's surface to a large extent. In addition, in the image-forming system, the quality of the image is greatly determined by the uniformity of the image's illumination distribution. However, in the practical optical system, affected by the factors such as field of view, false light and off axis and so on, the distribution of the image's illumination tends to be non uniform, so it is necessary to discuss the image plane's illumination in image-forming systems. In order to analyze the characteristics of the image-forming system at a full range, on the basis of photometry, the formulas to calculate the illumination of the imaging plane have been summarized by the numbers. Moreover, the relationship between the horizontal offset of the light source and the illumination of the image has been discussed in detail. After that, the influence of some key factors such as aperture angle, off-axis distance and horizontal offset on illumination of the image has been brought forward. Through numerical simulation, various theoretical curves of those key factors have been given. The results of the numerical simulation show that it is recommended to aggrandize the diameter of the exit pupil to increase the illumination of the image. The angle of view plays a negative role in the illumination distribution of the image, that is, the uniformity of the illumination distribution can be enhanced by compressing the angle of view. Lastly, it is proved that telecentric optical design is an effective way to advance the uniformity of the illumination distribution.

Robust uncertainty evaluation for system identification on distributed wireless platforms

Science.gov (United States)

Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

2016-04-01

Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

Point source identification in nonlinear advection–diffusion–reaction systems

International Nuclear Information System (INIS)

Mamonov, A V; Tsai, Y-H R

2013-01-01

We consider a problem of identification of point sources in time-dependent advection–diffusion systems with a nonlinear reaction term. The linear counterpart of the problem in question can be reduced to solving a system of nonlinear algebraic equations via the use of adjoint equations. We extend this approach by constructing an algorithm that solves the problem iteratively to account for the nonlinearity of the reaction term. We study the question of improving the quality of source identification by adding more measurements adaptively using the solution obtained previously with a smaller number of measurements. (paper)

Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images.

Science.gov (United States)

Okamoto, Takumi; Koide, Tetsushi; Sugi, Koki; Shimizu, Tatsuya; Anh-Tuan Hoang; Tamaki, Toru; Raytchev, Bisser; Kaneda, Kazufumi; Kominami, Yoko; Yoshida, Shigeto; Mieno, Hiroshi; Tanaka, Shinji

2015-08-01

With the increase of colorectal cancer patients in recent years, the needs of quantitative evaluation of colorectal cancer are increased, and the computer-aided diagnosis (CAD) system which supports doctor's diagnosis is essential. In this paper, a hardware design of type identification module in CAD system for colorectal endoscopic images with narrow band imaging (NBI) magnification is proposed for real-time processing of full high definition image (1920 × 1080 pixel). A pyramid style image segmentation with SVMs for multi-size scan windows, which can be implemented on an FPGA with small circuit area and achieve high accuracy, is proposed for actual complex colorectal endoscopic images.

Quantitative luminescence imaging system

Science.gov (United States)

Erwin, David N.; Kiel, Johnathan L.; Batishko, Charles R.; Stahl, Kurt A.

1990-01-01

The QLIS images and quantifies low-level chemiluminescent reactions in an electromagnetic field. It is capable of real time nonperturbing measurement and simultaneous recording of many biochemical and chemical reactions such as luminescent immunoassays or enzyme assays. The system comprises image transfer optics, a low-light level digitizing camera with image intensifying microchannel plates, an image process or, and a control computer. The image transfer optics may be a fiber image guide with a bend, or a microscope, to take the light outside of the RF field. Output of the camera is transformed into a localized rate of cumulative digitalized data or enhanced video display or hard-copy images. The system may be used as a luminescent microdosimetry device for radiofrequency or microwave radiation, as a thermal dosimeter, or in the dosimetry of ultra-sound (sonoluminescence) or ionizing radiation. It provides a near-real-time system capable of measuring the extremely low light levels from luminescent reactions in electromagnetic fields in the areas of chemiluminescence assays and thermal microdosimetry, and is capable of near-real-time imaging of the sample to allow spatial distribution analysis of the reaction. It can be used to instrument three distinctly different irradiation configurations, comprising (1) RF waveguide irradiation of a small Petri-dish-shaped sample cell, (2) RF irradiation of samples in a microscope for the microscopie imaging and measurement, and (3) RF irradiation of small to human body-sized samples in an anechoic chamber.

Music Identification System Using MPEG-7 Audio Signature Descriptors

Science.gov (United States)

You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

2013-01-01

This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

Variation in Microbial Identification System Accuracy for Yeast Identification Depending on Commercial Source of Sabouraud Dextrose Agar

OpenAIRE

Kellogg, James A.; Bankert, David A.; Chaturvedi, Vishnu

1999-01-01

The accuracy of the Microbial Identification System (MIS; MIDI, Inc.) for identification of yeasts to the species level was compared by using 438 isolates grown on prepoured BBL Sabouraud dextrose agar (SDA) and prepoured Remel SDA. Correct identification was observed for 326 (74%) of the yeasts cultured on BBL SDA versus only 214 (49%) of yeasts grown on Remel SDA (P < 0.001). The commercial source of the SDA used in the MIS procedure significantly influences the system’s accuracy.

A Framework for People Re-Identification in Multi-Camera Surveillance Systems

Science.gov (United States)

Ammar, Sirine; Zaghden, Nizar; Neji, Mahmoud

2017-01-01

People re-identification has been a very active research topic recently in computer vision. It is an important application in surveillance system with disjoint cameras. This paper is focused on the implementation of a human re-identification system. First the face of detected people is divided into three parts and some soft-biometric traits are…

Model Updating Nonlinear System Identification Toolbox, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — ZONA Technology (ZONA) proposes to develop an enhanced model updating nonlinear system identification (MUNSID) methodology that utilizes flight data with...

Challenges in parameter identification of large structural dynamic systems

International Nuclear Information System (INIS)

Koh, C.G.

2001-01-01

In theory, it is possible to determine the parameters of a structural or mechanical system by subjecting it to some dynamic excitation and measuring the response. Considerable research has been carried out in this subject area known as the system identification over the past two decades. Nevertheless, the challenges associated with numerical convergence are still formidable when the system is large in terms of the number of degrees of freedom and number of unknowns. While many methods work for small systems, the convergence becomes difficult, if not impossible, for large systems. In this keynote lecture, both classical and non-classical system identification methods for dynamic testing and vibration-based inspection are discussed. For classical methods, the extended Kalman filter (EKF) approach is used. On this basis, a substructural identification method has been developed as a strategy to deal with large structural systems. This is achieved by reducing the problem size, thereby significantly improving the numerical convergence and efficiency. Two versions of this method are presented each with its own merits. A numerical example of frame structure with 20 unknown parameters is illustrated. For non-classical methods, the Genetic Algorithm (GA) is shown to be applicable with relative ease due to its 'forward analysis' nature. The computational time is, however, still enormous for large structural systems due to the combinatorial explosion problem. A model GA method has been developed to address this problem and tested with considerable success on a relatively large system of 50 degrees of freedom, accounting for input and output noise effects. An advantages of this GA-based identification method is that the objective function can be defined in response measured. Numerical studies show that the method is relatively robust, as it does in response measured. Numerical studies show that the method is relatively robust, as it dos not require good initial guess and the

Rapid hyperspectral image classification to enable autonomous search systems

Directory of Open Access Journals (Sweden)

Raj Bridgelal

2016-11-01

Full Text Available The emergence of lightweight full-frame hyperspectral cameras is destined to enable autonomous search vehicles in the air, on the ground and in water. Self-contained and long-endurance systems will yield important new applications, for example, in emergency response and the timely identification of environmental hazards. One missing capability is rapid classification of hyperspectral scenes so that search vehicles can immediately take actions to verify potential targets. Onsite verifications minimise false positives and preclude the expense of repeat missions. Verifications will require enhanced image quality, which is achievable by either moving closer to the potential target or by adjusting the optical system. Such a solution, however, is currently impractical for small mobile platforms with finite energy sources. Rapid classifications with current methods demand large computing capacity that will quickly deplete the on-board battery or fuel. To develop the missing capability, the authors propose a low-complexity hyperspectral image classifier that approaches the performance of prevalent classifiers. This research determines that the new method will require at least 19-fold less computing capacity than the prevalent classifier. To assess relative performances, the authors developed a benchmark that compares a statistic of library endmember separability in their respective feature spaces.

Using wavelet multi-resolution nature to accelerate the identification of fractional order system

International Nuclear Information System (INIS)

Li Yuan-Lu; Meng Xiao; Ding Ya-Qing

2017-01-01

Because of the fractional order derivatives, the identification of the fractional order system (FOS) is more complex than that of an integral order system (IOS). In order to avoid high time consumption in the system identification, the least-squares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method. (paper)

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

Science.gov (United States)

Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

2018-05-01

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

PWL approximation of nonlinear dynamical systems, part II: identification issues

International Nuclear Information System (INIS)

De Feo, O; Storace, M

2005-01-01

This paper and its companion address the problem of the approximation/identification of nonlinear dynamical systems depending on parameters, with a view to their circuit implementation. The proposed method is based on a piecewise-linear approximation technique. In particular, this paper describes a black-box identification method based on state space reconstruction and PWL approximation, and applies it to some particularly significant dynamical systems (two topological normal forms and the Colpitts oscillator)

Image Guided Virtual Autopsy: An Adjunct with Radiographic and Computed Tomography Modalities - An Important Tool in Forensic Identification

Directory of Open Access Journals (Sweden)

Shalu Rai

2017-01-01

Full Text Available The forensic examination of dead bodies is very helpful in order to identify the person, cause of death, gender, and solving the mysterious cases. It includes a number of techniques, out of which autopsy is the primary investigation that is performed in every medicolegal case. Because of mutilation technologies, traditional autopsy technique is most disturbing in terms of emotions and rituals of relatives. The use of radiology in forensic science comprises performance, interpretation, and reporting of radiographs that is helpful in detecting those changes that are not clinically visible. Forensic radiology plays an important role for identification of humans in mass disasters, criminal investigations, and evaluation of cause of death. The introduction of radiological modalities in autopsy techniques is a complementary tool for forensic identification and is known as virtual autopsy. The advance imaging techniques such as computed tomography (CT and magnetic resonance imaging (MRI is used in virtual autopsy in order to visualize and reconstruct the internal organs to know the site, type, and depth of injury. This review elaborates the role of maxillofacial imaging in image-guided virtual autopsy.

Improved gravitational search algorithm for parameter identification of water turbine regulation system

International Nuclear Information System (INIS)

Chen, Zhihuan; Yuan, Xiaohui; Tian, Hao; Ji, Bin

2014-01-01

Highlights: • We propose an improved gravitational search algorithm (IGSA). • IGSA is applied to parameter identification of water turbine regulation system (WTRS). • WTRS is modeled by considering the impact of turbine speed on torque and water flow. • Weighted objective function strategy is applied to parameter identification of WTRS. - Abstract: Parameter identification of water turbine regulation system (WTRS) is crucial in precise modeling hydropower generating unit (HGU) and provides support for the adaptive control and stability analysis of power system. In this paper, an improved gravitational search algorithm (IGSA) is proposed and applied to solve the identification problem for WTRS system under load and no-load running conditions. This newly algorithm which is based on standard gravitational search algorithm (GSA) accelerates convergence speed with combination of the search strategy of particle swarm optimization and elastic-ball method. Chaotic mutation which is devised to stepping out the local optimal with a certain probability is also added into the algorithm to avoid premature. Furthermore, a new kind of model associated to the engineering practices is built and analyzed in the simulation tests. An illustrative example for parameter identification of WTRS is used to verify the feasibility and effectiveness of the proposed IGSA, as compared with standard GSA and particle swarm optimization in terms of parameter identification accuracy and convergence speed. The simulation results show that IGSA performs best for all identification indicators

Objective analysis of image quality of video image capture systems

Science.gov (United States)

Rowberg, Alan H.

1990-07-01

As Picture Archiving and Communication System (PACS) technology has matured, video image capture has become a common way of capturing digital images from many modalities. While digital interfaces, such as those which use the ACR/NEMA standard, will become more common in the future, and are preferred because of the accuracy of image transfer, video image capture will be the dominant method in the short term, and may continue to be used for some time because of the low cost and high speed often associated with such devices. Currently, virtually all installed systems use methods of digitizing the video signal that is produced for display on the scanner viewing console itself. A series of digital test images have been developed for display on either a GE CT9800 or a GE Signa MRI scanner. These images have been captured with each of five commercially available image capture systems, and the resultant images digitally transferred on floppy disk to a PC1286 computer containing Optimast' image analysis software. Here the images can be displayed in a comparative manner for visual evaluation, in addition to being analyzed statistically. Each of the images have been designed to support certain tests, including noise, accuracy, linearity, gray scale range, stability, slew rate, and pixel alignment. These image capture systems vary widely in these characteristics, in addition to the presence or absence of other artifacts, such as shading and moire pattern. Other accessories such as video distribution amplifiers and noise filters can also add or modify artifacts seen in the captured images, often giving unusual results. Each image is described, together with the tests which were performed using them. One image contains alternating black and white lines, each one pixel wide, after equilibration strips ten pixels wide. While some systems have a slew rate fast enough to track this correctly, others blur it to an average shade of gray, and do not resolve the lines, or give

BEEtag: A Low-Cost, Image-Based Tracking System for the Study of Animal Behavior and Locomotion.

Directory of Open Access Journals (Sweden)

James D Crall

Full Text Available A fundamental challenge common to studies of animal movement, behavior, and ecology is the collection of high-quality datasets on spatial positions of animals as they change through space and time. Recent innovations in tracking technology have allowed researchers to collect large and highly accurate datasets on animal spatiotemporal position while vastly decreasing the time and cost of collecting such data. One technique that is of particular relevance to the study of behavioral ecology involves tracking visual tags that can be uniquely identified in separate images or movie frames. These tags can be located within images that are visually complex, making them particularly well suited for longitudinal studies of animal behavior and movement in naturalistic environments. While several software packages have been developed that use computer vision to identify visual tags, these software packages are either (a not optimized for identification of single tags, which is generally of the most interest for biologists, or (b suffer from licensing issues, and therefore their use in the study of animal behavior has been limited. Here, we present BEEtag, an open-source, image-based tracking system in Matlab that allows for unique identification of individual animals or anatomical markers. The primary advantages of this system are that it (a independently identifies animals or marked points in each frame of a video, limiting error propagation, (b performs well in images with complex backgrounds, and (c is low-cost. To validate the use of this tracking system in animal behavior, we mark and track individual bumblebees (Bombus impatiens and recover individual patterns of space use and activity within the nest. Finally, we discuss the advantages and limitations of this software package and its application to the study of animal movement, behavior, and ecology.

Upport vector machines for nonlinear kernel ARMA system identification.

Science.gov (United States)

Martínez-Ramón, Manel; Rojo-Alvarez, José Luis; Camps-Valls, Gustavo; Muñioz-Marí, Jordi; Navia-Vázquez, Angel; Soria-Olivas, Emilio; Figueiras-Vidal, Aníbal R

2006-11-01

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA2K) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based system identification nonlinear models is presented, based on the use of composite Mercer's kernels. This general class can improve model flexibility by emphasizing the input-output cross information (SVM-ARMA4K), which leads to straightforward and natural combinations of implicit and explicit ARMA models (SVR-ARMA2K and SVR-ARMA4K). Capabilities of these different SVM-based system identification schemes are illustrated with two benchmark problems.

Transferability of Object-Oriented Image Analysis Methods for Slum Identification

Directory of Open Access Journals (Sweden)

Alfred Stein

2013-08-01

Full Text Available Updated spatial information on the dynamics of slums can be helpful to measure and evaluate progress of policies. Earlier studies have shown that semi-automatic detection of slums using remote sensing can be challenging considering the large variability in definition and appearance. In this study, we explored the potential of an object-oriented image analysis (OOA method to detect slums, using very high resolution (VHR imagery. This method integrated expert knowledge in the form of a local slum ontology. A set of image-based parameters was identified that was used for differentiating slums from non-slum areas in an OOA environment. The method was implemented on three subsets of the city of Ahmedabad, India. Results show that textural features such as entropy and contrast derived from a grey level co-occurrence matrix (GLCM and the size of image segments are stable parameters for classification of built-up areas and the identification of slums. Relation with classified slum objects, in terms of enclosed by slums and relative border with slums was used to refine classification. The analysis on three different subsets showed final accuracies ranging from 47% to 68%. We conclude that our method produces useful results as it allows including location specific adaptation, whereas generically applicable rulesets for slums are still to be developed.

Identification for automotive systems

CERN Document Server

Hjalmarsson, Håkan; Re, Luigi

2012-01-01

Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.

Music Identification System Using MPEG-7 Audio Signature Descriptors

Directory of Open Access Journals (Sweden)

Shingchern D. You

2013-01-01

Full Text Available This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system’s database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control.

Drug Delivery Systems for Imaging and Therapy of Parkinson's Disease.

Science.gov (United States)

Gunay, Mine Silindir; Ozer, A Yekta; Chalon, Sylvie

2016-01-01

Although a variety of therapeutic approaches are available for the treatment of Parkinson's disease, challenges limit effective therapy. Among these challenges are delivery of drugs through the blood brain barier to the target brain tissue and the side effects observed during long term administration of antiparkinsonian drugs. The use of drug delivery systems such as liposomes, niosomes, micelles, nanoparticles, nanocapsules, gold nanoparticles, microspheres, microcapsules, nanobubbles, microbubbles and dendrimers is being investigated for diagnosis and therapy. This review focuses on formulation, development and advantages of nanosized drug delivery systems which can penetrate the central nervous system for the therapy and/or diagnosis of PD, and highlights future nanotechnological approaches. It is esential to deliver a sufficient amount of either therapeutic or radiocontrast agents to the brain in order to provide the best possible efficacy or imaging without undesired degradation of the agent. Current treatments focus on motor symptoms, but these treatments generally do not deal with modifying the course of Parkinson's disease. Beyond pharmacological therapy, the identification of abnormal proteins such as α -synuclein, parkin or leucine-rich repeat serine/threonine protein kinase 2 could represent promising alternative targets for molecular imaging and therapy of Parkinson's disease. Nanotechnology and nanosized drug delivery systems are being investigated intensely and could have potential effect for Parkinson's disease. The improvement of drug delivery systems could dramatically enhance the effectiveness of Parkinson's Disease therapy and reduce its side effects.

High-speed biometrics ultrasonic system for 3D fingerprint imaging

Science.gov (United States)

Maev, Roman G.; Severin, Fedar

2012-10-01

The objective of this research is to develop a new robust fingerprint identification technology based upon forming surface-subsurface (under skin) ultrasonic 3D images of the finger pads. The presented work aims to create specialized ultrasonic scanning methods for biometric purposes. Preliminary research has demonstrated the applicability of acoustic microscopy for fingerprint reading. The additional information from internal skin layers and dermis structures contained in the scan can essentially improve confidence in the identification. Advantages of this system include high resolution and quick scanning time. Operating in pulse-echo mode provides spatial resolution up to 0.05 mm. Technology advantages of the proposed technology are the following: • Full-range scanning of the fingerprint area "nail to nail" (2.5 x 2.5 cm) can be done in less than 5 sec with a resolution of up to 1000 dpi. • Collection of information about the in-depth structure of the fingerprint realized by the set of spherically focused 50 MHz acoustic lens provide the resolution ~ 0.05 mm or better • In addition to fingerprints, this technology can identify sweat porous at the surface and under the skin • No sensitivity to the contamination of the finger's surface • Detection of blood velocity using Doppler effect can be implemented to distinguish living specimens • Utilization as polygraph device • Simple connectivity to fingerprint databases obtained with other techniques • The digitally interpolated images can then be enhanced allowing for greater resolution • Method can be applied to fingernails and underlying tissues, providing more information • A laboratory prototype of the biometrics system based on these described principles was designed, built and tested. It is the first step toward a practical implementation of this technique.

Integrating Satellite Image Identification and River Routing Simulation into the Groundwater Simulation of Chou-Shui Basin

Science.gov (United States)

Yao, Y.; Yang, S.; Chen, Y.; Chang, L.; Chiang, C.; Huang, C.; Chen, J.

2012-12-01

Many groundwater simulation models have been developed for Chou-Shui River alluvial fan which is one of the most important groundwater areas in Taiwan. However, the exchange quantity between Chou-Shui River, the major river in this area, and the groundwater system itself is seldom studied. In this study, the exchange is evaluated using a river package (RIV) in the groundwater simulation model, MODFLOW 2000. Several critical parameters and variables used in RIV such as wet area and river level for each cell below the Chou-Shui River are respectively determined by satellite image identification and HEC-RAS simulation. The monthly average of river levels obtained from four stations include Chang-Yun Bridge, Xi-Bin Bridge, Chi-Chiang Bridge and Si-Jou Bridge during 2008 and the river cross-section measured on December 2007 are used in the construction of HEC-RAS model. Four FORMOSAT multispectral satellite images respectively obtained on January 2008, April 2008, July 2008, and November 2008 are used to identify the wet area of Chou-Shui River during different seasons. Integrating the simulation level provided by HEC-RAS and the identification result are used as the assignment of RIV. First, based on the simulation results of HEC-RAS, the water level differences between flooding period and draught period are 1.4 (m) and 2.0 (m) for Xi-Bin Bridge station (downstream) and Chang-Yun Bridge station (upstream) respectively. Second, based on the identified results, the wet areas for four seasons are 24, 24, 40 and 12 (km2) respectively. The variation range of areas in 2008 is huge that the area for winter is just 30% of the area for summer. Third, based on the simulation of MODFLOW 2000 and RIV, the exchange between the river and the groundwater system is 414 million cubic meters which contains 526 for recharge to river and 112 for discharging from river during 2008. The total recharge includes river exchange and recharge from non-river area is 2023 million cubic meters. The

Multispectral system for medical fluorescence imaging

International Nuclear Information System (INIS)

Andersson, P.S.; Montan, S.; Svanberg, S.

1987-01-01

The principles of a powerful multicolor imaging system for tissue fluorescence diagnostics are discussed. Four individually spectrally filtered images are formed on a matrix detector by means of a split-mirror arrangement. The four images are processed in a computer, pixel by pixel, by means of mathematical operations, leading to an optimized contrast image, which enhances a selected feature. The system is being developed primarily for medical fluorescence imaging, but has wide applications in fluorescence, reflectance, and transmission monitoring related to a wide range of industrial and environmental problems. The system operation is described for the case of linear imaging on a diode array detector. Laser-induced fluorescence is used for cancer tumor and arteriosclerotic plaque demarcation using the contrast enhancement capabilities of this imaging system. Further examples of applications include fluorescing minerals and flames

Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

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Minghong She

2018-01-01

Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

Extremely secure identification documents

International Nuclear Information System (INIS)

Tolk, K.M.; Bell, M.

1997-09-01

The technology developed in this project uses biometric information printed on the document and public key cryptography to ensure that an adversary cannot issue identification documents to unauthorized individuals or alter existing documents to allow their use by unauthorized individuals. This process can be used to produce many types of identification documents with much higher security than any currently in use. The system is demonstrated using a security badge as an example. This project focused on the technologies requiring development in order to make the approach viable with existing badge printing and laminating technologies. By far the most difficult was the image processing required to verify that the picture on the badge had not been altered. Another area that required considerable work was the high density printed data storage required to get sufficient data on the badge for verification of the picture. The image processing process was successfully tested, and recommendations are included to refine the badge system to ensure high reliability. A two dimensional data array suitable for printing the required data on the badge was proposed, but testing of the readability of the array had to be abandoned due to reallocation of the budgeted funds by the LDRD office

33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

Science.gov (United States)

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Automatic Identification System Shipborne Equipment-Prince William Sound. 164.43 Section 164.43 Navigation and Navigable Waters COAST GUARD... Automatic Identification System Shipborne Equipment—Prince William Sound. (a) Until December 31, 2004, each...

Evaluation of an Airborne Remote Sensing Platform Consisting of Two Consumer-Grade Cameras for Crop Identification

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Jian Zhang

2016-03-01

Full Text Available Remote sensing systems based on consumer-grade cameras have been increasingly used in scientific research and remote sensing applications because of their low cost and ease of use. However, the performance of consumer-grade cameras for practical applications has not been well documented in related studies. The objective of this research was to apply three commonly-used classification methods (unsupervised, supervised, and object-based to three-band imagery with RGB (red, green, and blue bands and four-band imagery with RGB and near-infrared (NIR bands to evaluate the performance of a dual-camera imaging system for crop identification. Airborne images were acquired from a cropping area in Texas and mosaicked and georeferenced. The mosaicked imagery was classified using the three classification methods to assess the usefulness of NIR imagery for crop identification and to evaluate performance differences between the object-based and pixel-based methods. Image classification and accuracy assessment showed that the additional NIR band imagery improved crop classification accuracy over the RGB imagery and that the object-based method achieved better results with additional non-spectral image features. The results from this study indicate that the airborne imaging system based on two consumer-grade cameras used in this study can be useful for crop identification and other agricultural applications.

Model Updating Nonlinear System Identification Toolbox, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — ZONA Technology proposes to develop an enhanced model updating nonlinear system identification (MUNSID) methodology by adopting the flight data with state-of-the-art...

[Measures to prevent patient identification errors in blood collection/physiological function testing utilizing a laboratory information system].

Science.gov (United States)

Shimazu, Chisato; Hoshino, Satoshi; Furukawa, Taiji

2013-08-01

We constructed an integrated personal identification workflow chart using both bar code reading and an all in-one laboratory information system. The information system not only handles test data but also the information needed for patient guidance in the laboratory department. The reception terminals at the entrance, displays for patient guidance and patient identification tools at blood-sampling booths are all controlled by the information system. The number of patient identification errors was greatly reduced by the system. However, identification errors have not been abolished in the ultrasound department. After re-evaluation of the patient identification process in this department, we recognized that the major reason for the errors came from excessive identification workflow. Ordinarily, an ultrasound test requires patient identification 3 times, because 3 different systems are required during the entire test process, i.e. ultrasound modality system, laboratory information system and a system for producing reports. We are trying to connect the 3 different systems to develop a one-time identification workflow, but it is not a simple task and has not been completed yet. Utilization of the laboratory information system is effective, but is not yet perfect for patient identification. The most fundamental procedure for patient identification is to ask a person's name even today. Everyday checks in the ordinary workflow and everyone's participation in safety-management activity are important for the prevention of patient identification errors.

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

Science.gov (United States)

Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2014-05-01

By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

System Identification of a Non-Uniformly Sampled Multi-Rate System in Aluminium Electrolysis Cells

Directory of Open Access Journals (Sweden)

Håkon Viumdal

2014-07-01

Full Text Available Standard system identification algorithms are usually designed to generate mathematical models with equidistant sampling instants, that are equal for both input variables and output variables. Unfortunately, real industrial data sets are often disrupted by missing samples, variations of sampling rates in the different variables (also known as multi-rate systems, and intermittent measurements. In industries with varying events based maintenance or manual operational measures, intermittent measurements are performed leading to uneven sampling rates. Such is the case with aluminium smelters, where in addition the materials fed into the cell create even more irregularity in sampling. Both measurements and feeding are mostly manually controlled. A simplified simulation of the metal level in an aluminium electrolysis cell is performed based on mass balance considerations. System identification methods based on Prediction Error Methods (PEM such as Ordinary Least Squares (OLS, and the sub-space method combined Deterministic and Stochastic system identification and Realization (DSR, and its variants are applied to the model of a single electrolysis cell as found in the aluminium smelters. Aliasing phenomena due to large sampling intervals can be crucial in avoiding unsuitable models, but with knowledge about the system dynamics, it is easier to optimize the sampling performance, and hence achieve successful models. The results based on the simulation studies of molten aluminium height in the cells using the various algorithms give results which tally well with the synthetic data sets used. System identification on a smaller data set from a real plant is also implemented in this work. Finally, some concrete suggestions are made for using these models in the smelters.

Dental x-ray image segmentation

Science.gov (United States)

Said, Eyad; Fahmy, Gamal F.; Nassar, Diaa; Ammar, Hany

2004-08-01

Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. With the evolution in information technology and the huge volume of cases that need to be investigated by forensic specialists, it has become important to automate forensic identification systems. While, ante mortem (AM) identification, that is identification prior to death, is usually possible through comparison of many biometric identifiers, postmortem (PM) identification, that is identification after death, is impossible using behavioral biometrics (e.g. speech, gait). Moreover, under severe circumstances, such as those encountered in mass disasters (e.g. airplane crashers) or if identification is being attempted more than a couple of weeks postmortem, under such circumstances, most physiological biometrics may not be employed for identification, because of the decay of soft tissues of the body to unidentifiable states. Therefore, a postmortem biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features. In this paper we present an over view about an automated dental identification system for Missing and Unidentified Persons. This dental identification system can be used by both law enforcement and security agencies in both forensic and biometric identification. We will also present techniques for dental segmentation of X-ray images. These techniques address the problem of identifying each individual tooth and how the contours of each tooth are extracted.

Automated identification of retained surgical items in radiological images

Science.gov (United States)

Agam, Gady; Gan, Lin; Moric, Mario; Gluncic, Vicko

2015-03-01

Retained surgical items (RSIs) in patients is a major operating room (OR) patient safety concern. An RSI is any surgical tool, sponge, needle or other item inadvertently left in a patients body during the course of surgery. If left undetected, RSIs may lead to serious negative health consequences such as sepsis, internal bleeding, and even death. To help physicians efficiently and effectively detect RSIs, we are developing computer-aided detection (CADe) software for X-ray (XR) image analysis, utilizing large amounts of currently available image data to produce a clinically effective RSI detection system. Physician analysis of XRs for the purpose of RSI detection is a relatively lengthy process that may take up to 45 minutes to complete. It is also error prone due to the relatively low acuity of the human eye for RSIs in XR images. The system we are developing is based on computer vision and machine learning algorithms. We address the problem of low incidence by proposing synthesis algorithms. The CADe software we are developing may be integrated into a picture archiving and communication system (PACS), be implemented as a stand-alone software application, or be integrated into portable XR machine software through application programming interfaces. Preliminary experimental results on actual XR images demonstrate the effectiveness of the proposed approach.

Event storm detection and identification in communication systems

International Nuclear Information System (INIS)

Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

2006-01-01

Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

IDENTIFICATION ASPECT OF METHODOLOGY DESIGN OF CONTROL SYSTEM TIME-VARIANT PROCESS

Directory of Open Access Journals (Sweden)

M. M. Blagoveshchenskaia

2014-01-01

Full Text Available Summary. Specificity of a food manufacture demands perfection of automatic control systems of processes in devices, units and installations. Creation of an adaptive control system by technological process of a food on the basis of model of control object it is necessary to carry out the additional analysis for choice algorithm of identification on real enough to representative sample of input data and output signal/data. In article on the basis of simulation it is analyzed over 53 algorithms of recurrent identification plus the basic modifications of these algorithms by 47 criteria for time-varying multivariable linear dynamic objects. On the basis of this analysis for engineering practice for a considered class of objects some algorithms are recommended. Possibilities of the software suite having for today the fullest set of parametrical identification algorithms are discussed. For given specific conditions of comparison in the package identification algorithms for identification of stationary coefficients in the equation object of the most effective were: Yzerman-1, Kaczmarz, Nagumo-Noda, Rastrigin, Kalman filter, the forgetting factor, Zipkin. When pointwise object - Kaczmarz, Nagumo-Noda, Kalman filter; showed the best result identification algorithm-Nagumo Noda.

Single camera photogrammetry system for EEG electrode identification and localization.

Science.gov (United States)

Baysal, Uğur; Sengül, Gökhan

2010-04-01

In this study, photogrammetric coordinate measurement and color-based identification of EEG electrode positions on the human head are simultaneously implemented. A rotating, 2MP digital camera about 20 cm above the subject's head is used and the images are acquired at predefined stop points separated azimuthally at equal angular displacements. In order to realize full automation, the electrodes have been labeled by colored circular markers and an electrode recognition algorithm has been developed. The proposed method has been tested by using a plastic head phantom carrying 25 electrode markers. Electrode locations have been determined while incorporating three different methods: (i) the proposed photogrammetric method, (ii) conventional 3D radiofrequency (RF) digitizer, and (iii) coordinate measurement machine having about 6.5 mum accuracy. It is found that the proposed system automatically identifies electrodes and localizes them with a maximum error of 0.77 mm. It is suggested that this method may be used in EEG source localization applications in the human brain.

Transfer function analysis of radiographic imaging systems

International Nuclear Information System (INIS)

Metz, C.E.; Doi, K.

1979-01-01

The theoretical and experimental aspects of the techniques of transfer function analysis used in radiographic imaging systems are reviewed. The mathematical principles of transfer function analysis are developed for linear, shift-invariant imaging systems, for the relation between object and image and for the image due to a sinusoidal plane wave object. The other basic mathematical principle discussed is 'Fourier analysis' and its application to an input function. Other aspects of transfer function analysis included are alternative expressions for the 'optical transfer function' of imaging systems and expressions are derived for both serial and parallel transfer image sub-systems. The applications of transfer function analysis to radiographic imaging systems are discussed in relation to the linearisation of the radiographic imaging system, the object, the geometrical unsharpness, the screen-film system unsharpness, other unsharpness effects and finally noise analysis. It is concluded that extensive theoretical, computer simulation and experimental studies have demonstrated that the techniques of transfer function analysis provide an accurate and reliable means for predicting and understanding the effects of various radiographic imaging system components in most practical diagnostic medical imaging situations. (U.K.)

Identification of mineral deposits in the brain on radiological images: a systematic review

International Nuclear Information System (INIS)

DelValdes Hernandez, Maria; Maconick, Lucy C.; Tan, Elizabeth M.J.; Wardlaw, Joanna M.

2012-01-01

MRI has allowed the study of mineral deposition in the brain throughout life and in disease. However, studies differ in their reporting of minerals on MRI for reasons that are unclear. We conducted a systematic review from 1985 to July 2011 to determine the appearance of iron, calcium, copper and manganese on MRI and CT and their reliability. We assessed which imaging investigations provided the most consistent results compared with histology. Of 325 papers on minerals imaging, we included 46 studies that confirmed findings either directly or indirectly using a non-imaging method such as histology. Within this group, there was inconsistency in the identification of iron probably because of changes in its paramagnetic properties during its degradation. Iron appeared consistently hypointense only on T2*-weighted MRI, and along with calcified areas, hyperattenuated on CT. Appearance of copper, calcium and manganese, although consistently reported as hyperintense on T1-weighted MRI, was confirmed histologically in few studies. On T2-weighted imaging, calcified areas were always reported as hypointense, while the appearance of iron depended on the concentration, location and degradation stage. More work is required to improve the reliability of imaging methods to detect and differentiate brain mineral deposition accurately. (orig.)

Structural System Identification with Extended Kalman Filter and Orthogonal Decomposition of Excitation

Directory of Open Access Journals (Sweden)

Y. Ding

2014-01-01

Full Text Available Both the structural parameter and external excitation have coupling influence on structural response. A new system identification method in time domain is proposed to simultaneously evaluate structural parameter and external excitation. The method can be used for linear and hysteresis nonlinear structural condition assessment based on incomplete structural responses. In this method, the structural excitation is decomposed by orthogonal approximation. With this approximation, the strongly time-variant excitation identification is transformed to gentle time-variant, even constant parameters identification. Then the extended Kalman filter is applied to simultaneously identify state vector including the structural parameters and excitation orthogonal parameters in state space based on incomplete measurements. The proposed method is validated numerically with the simulation of three-story linear and nonlinear structures subject to external force. The external force on the top floor and the structural parameters are simultaneously identified with the proposed system identification method. Results from both simulations indicate that the proposed method is capable of identifing the dynamic load and structural parameters fairly accurately with contaminated incomplete measurement for both of the linear and nonlinear structural systems.

Investigation of innovative radiation imaging method and system for radiological environments

Energy Technology Data Exchange (ETDEWEB)

Nguyen, H. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Joung, J., E-mail: jinhun.joung@nucaremed.com [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Nucare, Inc., Incheon (Korea, Republic of); Kim, Y. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of); Nucare, Inc., Incheon (Korea, Republic of); Lee, K. [School of Biomedical Engineering, Korea University, Seoul (Korea, Republic of)

2017-03-01

demonstrated imaging of 3D space, which is the most general and fundamental task in the field of radiological environment imaging. The experiments show quite promising results. In addition, the method is able to provide quantitative information about each distribution, including isotope identification, activity concentration, and the size and shape of radiation sources. Our future studies include employing other detector modules and collimators and developing systems for other applications, such as container truck and conveyor inspections.

Identification of systems with distributed parameters

International Nuclear Information System (INIS)

Moret, J.M.

1990-10-01

The problem of finding a model for the dynamical response of a system with distributed parameters based on measured data is addressed. First a mathematical formalism is developed in order to obtain the specific properties of such a system. Then a linear iterative identification algorithm is proposed that includes these properties, and that produces better results than usual non linear minimisation techniques. This algorithm is further improved by an original data decimation that allow to artificially increase the sampling period without losing between sample information. These algorithms are tested with real laboratory data

Dynamic MR imaging of the musculoskeletal system

International Nuclear Information System (INIS)

Shah, A.S.; Hylton, H.; Hentz, V.R.; Schattner, P.

1991-01-01

This paper reports on dynamic MR imaging which is an MR technique that allows imaging of the musculoskeletal system in motion. Current methods for observing the articulation of muscles and joints are limited to acquisition of stationary images at different spatial orientations. These images are then replayed from computer memory to simulate motion. Unlike stationary acquisition, dynamic MR imaging allows the volume of interest to be subjected to motion and dynamic stress, which is important for detecting stress-induced pathology. To demonstrate the utility of dynamic MR imaging, a system for imaging a moving wrist has been developed. The system consists of apparatus capable of providing simultaneous radialulnar deviation and flexion-extension, and hardware for system control and acquisition gating. The apparatus is mounted on the patient bed and is transferable to a variety of standard clinical MR imaging systems. Images were obtained during motion, and the ability of dynamic MR imaging to accurately image the moving wrist with very little motion artifact was demonstrated

Use of infrared hyperspectral imaging as an aid for paint identification

Directory of Open Access Journals (Sweden)

A. Polak

2016-10-01

Full Text Available Art authentication is a complicated process that often requires the extensive study of high value objects. Although a series of non-destructive techniques is already available for art scientists, new techniques, extending current possibilities, are still required. In this paper, the use of a novel mid-infrared tunable imager is proposed as an active hyperspectral imaging system for art work analysis. The system provides access to a range of wavelengths in the electromagnetic spectrum (2500–3750 nm which are otherwise difficult to access using conventional hyperspectral imaging (HSI equipment. The use of such a tool could be beneficial if applied to the paint classification problem and could help analysts map the diversity of pigments within a given painting. The performance of this tool is demonstrated and compared with a conventional, off-the-shelf HSI system operating in the near infrared spectral region (900–1700 nm. Various challenges associated with laser-based imaging are demonstrated and solutions to these challenges as well as the results of applying classification algorithms to datasets captured using both HSI systems are presented. While the conventional HSI system provides data in which more pigments can be accurately classified, the result of applying the proposed laser-based imaging system demonstrates the validity of this technique for application in art authentication tasks.

78 FR 58785 - Unique Device Identification System

Science.gov (United States)

2013-09-24

... the UDI system because they are controlled in the supply chain by the kit rather than by constituent... reduce existing obstacles to the adequate identification of medical devices used in the United States. By... stated, ``We support FDA's objective to substantially reduce existing obstacles to the adequate...

Time-Delay System Identification Using Genetic Algorithm

DEFF Research Database (Denmark)

Yang, Zhenyu; Seested, Glen Thane

2013-01-01

problem through an identification approach using the real coded Genetic Algorithm (GA). The desired FOPDT/SOPDT model is directly identified based on the measured system's input and output data. In order to evaluate the quality and performance of this GA-based approach, the proposed method is compared...

Data based identification and prediction of nonlinear and complex dynamical systems

Science.gov (United States)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

Data based identification and prediction of nonlinear and complex dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

2016-07-12

dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

Data based identification and prediction of nonlinear and complex dynamical systems

International Nuclear Information System (INIS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-01-01

dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

The design of the optical components and gas control systems of the CERN Omega Ring Imaging Cerenkov Detector

International Nuclear Information System (INIS)

Apsimon, R.J.; Cowell, J.; Flower, P.S.

1985-06-01

A large Ring Imaging Cerenkov Detector (RICH) has been commissioned for use at the CERN Omega Spectrometer. The general design of the device is discussed, and the dependence of the attainable spatial resolution and range of particle identification on its optical parameters is illustrated. The construction and performance of the major optical components and gas systems of the detector are also described. (author)

Magnetic resonance imaging identification of muscular and ligamentous structures of the female pelvic floor; Identificacao das estruturas musculo-ligamentares do assoalho pelvico feminino na ressonancia magnetica

Energy Technology Data Exchange (ETDEWEB)

Bezerra, Maria Rita Lima; Soares, Adriano Fleury F.; Faintuch, Salomao; Goldman, Suzan Menasce; Ajzen, Sergio A.; D' Ippolito, Giuseppe; Szejnfeld, Jacob [Universidade Federal de Sao Paulo (UNIFESP/EPM), Sao Paulo, SP (Brazil). Dept. de Diagnostico por Imagem]. E-mail: mrcfc@ig.com.br; Girao, Manoel [Universidade Federal de Sao Paulo (UNIFESP/EPM), Sao Paulo, SP (Brazil). Dept. de Ginecologia

2001-12-01

The objective was to determine the frequency and to assess the interobserver agreement of identification of muscular and ligamentous pelvic floor structures using magnetic resonance imaging. The method: twenty asymptomatic female volunteers (aged 20-80 years old; mean: 50) were submitted to magnetic resonance imaging (1.5 T) examinations of the pelvis. Turbo spin-echo sequences were employed to obtain T1 and T2 weighted images on axial and sagittal planes. Two independent observers evaluated the scans in order to identify the levator ani (coccygeal, pubococcygeal, iliococcygeal and puborectalis muscles), obturatorius internus and urethral sphincter muscles, and the pubovesical and pubourethral ligaments. The frequency and the interobserver agreement of the identification of the anatomical structures were assessed (kappa statistic - {kappa}). The results: the frequency of identification of the structures ranged from 50 to 100%, and was slightly lower for identification of the ligaments. Interobserver agreement was as follows: levator ani and obturatorius internus muscle ({kappa}=1), pubococcygeal ({kappa}=0.62), iliococcygeal ({kappa}=0.86), puborectalis ({kappa}= 0.27), coccygeal ({kappa}=0) and urethral sphincter muscles ({kappa}=1), pubovesical ({kappa}=0.50) and pubourethral ({kappa}=0.58) ligaments. The conclusion: magnetic resonance imaging of the pelvis allowed precise identification of the main muscular and ligamentous pelvic floor structures in most individuals, whereas interobserver agreement was considered good. (author)

Stability Analysis of Neural Networks-Based System Identification

Directory of Open Access Journals (Sweden)

Talel Korkobi

2008-01-01

Full Text Available This paper treats some problems related to nonlinear systems identification. A stability analysis neural network model for identifying nonlinear dynamic systems is presented. A constrained adaptive stable backpropagation updating law is presented and used in the proposed identification approach. The proposed backpropagation training algorithm is modified to obtain an adaptive learning rate guarantying convergence stability. The proposed learning rule is the backpropagation algorithm under the condition that the learning rate belongs to a specified range defining the stability domain. Satisfying such condition, unstable phenomena during the learning process are avoided. A Lyapunov analysis leads to the computation of the expression of a convenient adaptive learning rate verifying the convergence stability criteria. Finally, the elaborated training algorithm is applied in several simulations. The results confirm the effectiveness of the CSBP algorithm.

Reduced Complexity Volterra Models for Nonlinear System Identification

Directory of Open Access Journals (Sweden)

Hacıoğlu Rıfat

2001-01-01

Full Text Available A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter′s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a Fixed Pole Expansion Technique (FPET within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed in the paper.

An imaging system for a gamma camera

International Nuclear Information System (INIS)

Miller, D.W.; Gerber, M.S.

1980-01-01

A detailed description is given of a novel gamma camera which is designed to produce superior images than conventional cameras used in nuclear medicine. The detector consists of a solid state detector (e.g. germanium) which is formed to have a plurality of discrete components to enable 2-dimensional position identification. Details of the electronic processing circuits are given and the problems and limitations introduced by noise are discussed in full. (U.K.)

Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system.

Science.gov (United States)

Hannan, M A; Arebey, Maher; Begum, R A; Basri, Hassan

2011-12-01

This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity. Copyright © 2011 Elsevier Ltd. All rights reserved.

Estimation of identification limit for a small-type OSL dosimeter on the medical images by measurement of X-ray spectra.

Science.gov (United States)

Takegami, Kazuki; Hayashi, Hiroaki; Okino, Hiroki; Kimoto, Natsumi; Maehata, Itsumi; Kanazawa, Yuki; Okazaki, Tohru; Hashizume, Takuya; Kobayashi, Ikuo

2016-07-01

Our aim in this study is to derive an identification limit on a dosimeter for not disturbing a medical image when patients wear a small-type optically stimulated luminescence (OSL) dosimeter on their bodies during X-ray diagnostic imaging. For evaluation of the detection limit based on an analysis of X-ray spectra, we propose a new quantitative identification method. We performed experiments for which we used diagnostic X-ray equipment, a soft-tissue-equivalent phantom (1-20 cm), and a CdTe X-ray spectrometer assuming one pixel of the X-ray imaging detector. Then, with the following two experimental settings, corresponding X-ray spectra were measured with 40-120 kVp and 0.5-1000 mAs at a source-to-detector distance of 100 cm: (1) X-rays penetrating a soft-tissue-equivalent phantom with the OSL dosimeter attached directly on the phantom, and (2) X-rays penetrating only the soft-tissue-equivalent phantom. Next, the energy fluence and errors in the fluence were calculated from the spectra. When the energy fluence with errors concerning these two experimental conditions was estimated to be indistinctive, we defined the condition as the OSL dosimeter not being identified on the X-ray image. Based on our analysis, we determined the identification limit of the dosimeter. We then compared our results with those for the general irradiation conditions used in clinics. We found that the OSL dosimeter could not be identified under the irradiation conditions of abdominal and chest radiography, namely, one can apply the OSL dosimeter to measurement of the exposure dose in the irradiation field of X-rays without disturbing medical images.

Mechanics of bioinspired imaging systems

Directory of Open Access Journals (Sweden)

Zhengwei Li

2016-01-01

Full Text Available Imaging systems in nature have attracted a lot of research interest due to their superior optical and imaging characteristics. Recent advancements in materials science, mechanics, and stretchable electronics have led to successful development of bioinspired cameras that resemble the structures and functions of biological light-sensing organs. In this review, we discuss some recent progresses in mechanics of bioinspired imaging systems, including tunable hemispherical eyeball camera and artificial compound eye camera. The mechanics models and results reviewed in this article can provide efficient tools for design and optimization of such systems, as well as other related optoelectronic systems that combine rigid elements with soft substrates.

FY1995 development of a endoscopic surgical system utilizing multi-modal functional images; 1995 nendo tashu kino gazo wo mochiiru teishinshu naishikyo shujutsu system no kaihatsu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-05-01

The purpose of this study is to develop an endoscope system for neurosurgery that can provide not only conventional endoscopic images but also ultraviolet-visible spectra, fluorescence spectra, near infrared spectra, and ultra-soundimages of tissue aiming for real-time identification of pathological tissue. The system also incorporates surgical manipulator and devices such as micro forceps and laser surgical instruments for endoscopic image guided surgery. Surgical Manipulator should be a high performance and easy to operate surgical instrument as well as conventional surgical tools such as scissors and knife. Since living tissue deforms during surgical operation, pre-operative three dimensional information for registration of pathological tissue should be modified based on information obtained during surgery. Thus surgical manipulator should be operated under guidance of surgeon's observation. Consequently, surgical manipulator should have various types of imaging and measurement devices such as an endoscope and an ultrasound imaging probe at its end effectors. Based on this concept, a prototype of a new multi channel surgical manipulator system CM cube (CM3, Computer aided Micro Multichannel Manipulator) that has various types of imaging and measurement devices such as ultra-violet-visible camera for spectroscopic measurement, ultra-sound imaging probe, three dimensional endoscope, together with micro surgical instruments and laser surgical systems has been developed. Its performance was evaluated through in vitro/in vivo experiments and clinical application. (NEDO)

High sensitivity optical molecular imaging system

Science.gov (United States)

An, Yu; Yuan, Gao; Huang, Chao; Jiang, Shixin; Zhang, Peng; Wang, Kun; Tian, Jie

2018-02-01

Optical Molecular Imaging (OMI) has the advantages of high sensitivity, low cost and ease of use. By labeling the regions of interest with fluorescent or bioluminescence probes, OMI can noninvasively obtain the distribution of the probes in vivo, which play the key role in cancer research, pharmacokinetics and other biological studies. In preclinical and clinical application, the image depth, resolution and sensitivity are the key factors for researchers to use OMI. In this paper, we report a high sensitivity optical molecular imaging system developed by our group, which can improve the imaging depth in phantom to nearly 5cm, high resolution at 2cm depth, and high image sensitivity. To validate the performance of the system, special designed phantom experiments and weak light detection experiment were implemented. The results shows that cooperated with high performance electron-multiplying charge coupled device (EMCCD) camera, precision design of light path system and high efficient image techniques, our OMI system can simultaneously collect the light-emitted signals generated by fluorescence molecular imaging, bioluminescence imaging, Cherenkov luminance and other optical imaging modality, and observe the internal distribution of light-emitting agents fast and accurately.