A video multitracking system for quantification of individual behavior in a large fish shoal: advantages and limits.

PubMed

Delcourt, Johann; Becco, Christophe; Vandewalle, Nicolas; Poncin, Pascal

2009-02-01

The capability of a new multitracking system to track a large number of unmarked fish (up to 100) is evaluated. This system extrapolates a trajectory from each individual and analyzes recorded sequences that are several minutes long. This system is very efficient in statistical individual tracking, where the individual's identity is important for a short period of time in comparison with the duration of the track. Individual identification is typically greater than 99%. Identification is largely efficient (more than 99%) when the fish images do not cross the image of a neighbor fish. When the images of two fish merge (occlusion), we consider that the spot on the screen has a double identity. Consequently, there are no identification errors during occlusions, even though the measurement of the positions of each individual is imprecise. When the images of these two merged fish separate (separation), individual identification errors are more frequent, but their effect is very low in statistical individual tracking. On the other hand, in complete individual tracking, where individual fish identity is important for the entire trajectory, each identification error invalidates the results. In such cases, the experimenter must observe whether the program assigns the correct identification, and, when an error is made, must edit the results. This work is not too costly in time because it is limited to the separation events, accounting for fewer than 0.1% of individual identifications. Consequently, in both statistical and rigorous individual tracking, this system allows the experimenter to gain time by measuring the individual position automatically. It can also analyze the structural and dynamic properties of an animal group with a very large sample, with precision and sampling that are impossible to obtain with manual measures.

Palmprint identification using FRIT

NASA Astrophysics Data System (ADS)

Kisku, D. R.; Rattani, A.; Gupta, P.; Hwang, C. J.; Sing, J. K.

2011-06-01

This paper proposes a palmprint identification system using Finite Ridgelet Transform (FRIT) and Bayesian classifier. FRIT is applied on the ROI (region of interest), which is extracted from palmprint image, to extract a set of distinctive features from palmprint image. These features are used to classify with the help of Bayesian classifier. The proposed system has been tested on CASIA and IIT Kanpur palmprint databases. The experimental results reveal better performance compared to all well known systems.

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing

PubMed Central

Wang, Xuefeng

2017-01-01

This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees. PMID:28749977

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing.

PubMed

Wu, Chunyan; Wang, Xuefeng

2017-01-01

This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees.

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

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Non-image-intensified fluoroscopic x-ray system... fluoroscopic x-ray system. (a) Identification. A non-image-intensified fluoroscopic x-ray system is a device... of x-radiation into a visible image. This generic type of device may include signal analysis and...

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

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Non-image-intensified fluoroscopic x-ray system... fluoroscopic x-ray system. (a) Identification. A non-image-intensified fluoroscopic x-ray system is a device... of x-radiation into a visible image. This generic type of device may include signal analysis and...

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

21 CFR 892.1550 - Ultrasonic pulsed doppler imaging system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Ultrasonic pulsed doppler imaging system. 892.1550... system. (a) Identification. An ultrasonic pulsed doppler imaging system is a device that combines the... determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic...

A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format.

PubMed

Monteiro, Eriksson; Costa, Carlos; Oliveira, José Luís

2017-05-01

Clinical data sharing between healthcare institutions, and between practitioners is often hindered by privacy protection requirements. This problem is critical in collaborative scenarios where data sharing is fundamental for establishing a workflow among parties. The anonymization of patient information burned in DICOM images requires elaborate processes somewhat more complex than simple de-identification of textual information. Usually, before sharing, there is a need for manual removal of specific areas containing sensitive information in the images. In this paper, we present a pipeline for ultrasound medical image de-identification, provided as a free anonymization REST service for medical image applications, and a Software-as-a-Service to streamline automatic de-identification of medical images, which is freely available for end-users. The proposed approach applies image processing functions and machine-learning models to bring about an automatic system to anonymize medical images. To perform character recognition, we evaluated several machine-learning models, being Convolutional Neural Networks (CNN) selected as the best approach. For accessing the system quality, 500 processed images were manually inspected showing an anonymization rate of 89.2%. The tool can be accessed at https://bioinformatics.ua.pt/dicom/anonymizer and it is available with the most recent version of Google Chrome, Mozilla Firefox and Safari. A Docker image containing the proposed service is also publicly available for the community.

Fimag: the United Kingdom disaster victim/forensic identification imaging system.

PubMed

Rutty, Guy N; Robinson, Claire; Morgan, Bruno; Black, Sue; Adams, Catherine; Webster, Philip

2009-11-01

Imaging is an integral diagnostic tool in mass fatality investigations undertaken traditionally by plain X-rays, fluoroscopy, and dental radiography. However, little attention has been given to appropriate image reporting, secure data transfer and storage particularly in relation to the need to meet stringent judicial requirements. Notwithstanding these limitations, it is the risk associated with the safe handling and investigation of contaminated fatalities which is providing new challenges for mass fatality radiological imaging. Mobile multi-slice computed tomography is an alternative to these traditional modalities as it provides a greater diagnostic yield and an opportunity to address the requirements of the criminal justice system. We present a new national disaster victim/forensic identification imaging system--Fimag--which is applicable for both contaminated and non-contaminated mass fatality imaging and addresses the issues of judicial reporting. We suggest this system opens a new era in radiological diagnostics for mass fatalities.

49 CFR 579.4 - Terminology.

Code of Federal Regulations, 2013 CFR

2013-10-01

... term Tire Identification Number (TIN) is the “tire identification number” described in § 574.5 of this..., fasteners, etc.). Backover prevention system means a system that has a visual image of the area directly...

A biometric identification system based on eigenpalm and eigenfinger features.

PubMed

Ribaric, Slobodan; Fratric, Ivan

2005-11-01

This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

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

PubMed

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.

TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapadia, A; Morris, R; Albanese, K

Purpose: We have previously described the development and testing of a coherent-scatter spectral imaging system for identification of cancer. Our prior evaluations were performed using either tissue surrogate phantoms or formalin-fixed tissue obtained from pathology. Here we present the first results from a scatter imaging study using fresh breast tumor tissues obtained through surgical excision. Methods: A coherent-scatter imaging system was built using a clinical X-ray tube, photon counting detectors, and custom-designed coded-apertures. System performance was characterized using calibration phantoms of biological materials. Fresh breast tumors were obtained from patients undergoing mastectomy and lumpectomy surgeries for breast cancer. Each specimenmore » was vacuum-sealed, scanned using the scatter imaging system, and then sent to pathology for histological workup. Scatter images were generated separately for each tissue specimen and analyzed to identify voxels containing malignant tissue. The images were compared against histological analysis (H&E + pathologist identification of tumors) to assess the match between scatter-based and histological diagnosis. Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2–3 mm, and the total scan time for each specimen was under 15 minutes. Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It presents the first results from coherent scatter imaging of fresh (unfixed) breast tissue using our coded-aperture scatter imaging approach for cancer identification.« less

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

Microscopic optical path length difference and polarization measurement system for cell analysis

NASA Astrophysics Data System (ADS)

Satake, H.; Ikeda, K.; Kowa, H.; Hoshiba, T.; Watanabe, E.

2018-03-01

In recent years, noninvasive, nonstaining, and nondestructive quantitative cell measurement techniques have become increasingly important in the medical field. These cell measurement techniques enable the quantitative analysis of living cells, and are therefore applied to various cell identification processes, such as those determining the passage number limit during cell culturing in regenerative medicine. To enable cell measurement, we developed a quantitative microscopic phase imaging system based on a Mach-Zehnder interferometer that measures the optical path length difference distribution without phase unwrapping using optical phase locking. The applicability of our phase imaging system was demonstrated by successful identification of breast cancer cells amongst normal cells. However, the cell identification method using this phase imaging system exhibited a false identification rate of approximately 7%. In this study, we implemented a polarimetric imaging system by introducing a polarimetric module to one arm of the Mach-Zehnder interferometer of our conventional phase imaging system. This module was comprised of a quarter wave plate and a rotational polarizer on the illumination side of the sample, and a linear polarizer on the optical detector side. In addition, we developed correction methods for the measurement errors of the optical path length and birefringence phase differences that arose through the influence of elements other than cells, such as the Petri dish. As the Petri dish holding the fluid specimens was transparent, it did not affect the amplitude information; however, the optical path length and birefringence phase differences were affected. Therefore, we proposed correction of the optical path length and birefringence phase for the influence of elements other than cells, as a prerequisite for obtaining highly precise phase and polarimetric images.

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

NASA Astrophysics Data System (ADS)

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.

The clinical information system GastroBase: integration of image processing and laboratory communication.

PubMed

Kocna, P

1995-01-01

GastroBase, a clinical information system, incorporates patient identification, medical records, images, laboratory data, patient history, physical examination, and other patient-related information. Program modules are written in C; all data is processed using Novell-Btrieve data manager. Patient identification database represents the main core of this information systems. A graphic library developed in the past year and graphic modules with a special video-card enables the storing, archiving, and linking of different images to the electronic patient-medical-record. GastroBase has been running for more than four years in daily routine and the database contains more than 25,000 medical records and 1,500 images. This new version of GastroBase is now incorporated into the clinical information system of University Clinic in Prague.

Identification Of Cells With A Compact Microscope Imaging System With Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark (Inventor)

2006-01-01

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking mic?oscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

The Gini Coefficient as a Tool for Image Family Idenitification in Strong Lensing Systems with Multiple Images

NASA Astrophysics Data System (ADS)

Florian, Michael K.; Gladders, Michael D.; Li, Nan; Sharon, Keren

2016-01-01

The sample of cosmological strong lensing systems has been steadily growing in recent years and with the advent of the next generation of space-based survey telescopes, the sample will reach into the thousands. The accuracy of strong lens models relies on robust identification of multiple image families of lensed galaxies. For the most massive lenses, often more than one background galaxy is magnified and multiply imaged, and even in the cases of only a single lensed source, identification of counter images is not always robust. Recently, we have shown that the Gini coefficient in space-telescope-quality imaging is a measurement of galaxy morphology that is relatively well-preserved by strong gravitational lensing. Here, we investigate its usefulness as a diagnostic for the purposes of image family identification and show that it can remove some of the degeneracies encountered when using color as the sole diagnostic, and can do so without the need for additional observations since whenever a color is available, two Gini coefficients are as well.

Comparison of fingerprint and facial biometric verification technologies for user access and patient identification in a clinical environment

NASA Astrophysics Data System (ADS)

Guo, Bing; Zhang, Yu; Documet, Jorge; Liu, Brent; Lee, Jasper; Shrestha, Rasu; Wang, Kevin; Huang, H. K.

2007-03-01

As clinical imaging and informatics systems continue to integrate the healthcare enterprise, the need to prevent patient mis-identification and unauthorized access to clinical data becomes more apparent especially under the Health Insurance Portability and Accountability Act (HIPAA) mandate. Last year, we presented a system to track and verify patients and staff within a clinical environment. This year, we further address the biometric verification component in order to determine which Biometric system is the optimal solution for given applications in the complex clinical environment. We install two biometric identification systems including fingerprint and facial recognition systems at an outpatient imaging facility, Healthcare Consultation Center II (HCCII). We evaluated each solution and documented the advantages and pitfalls of each biometric technology in this clinical environment.

Comparison of sonochemiluminescence images using image analysis techniques and identification of acoustic pressure fields via simulation.

PubMed

Tiong, T Joyce; Chandesa, Tissa; Yap, Yeow Hong

2017-05-01

One common method to determine the existence of cavitational activity in power ultrasonics systems is by capturing images of sonoluminescence (SL) or sonochemiluminescence (SCL) in a dark environment. Conventionally, the light emitted from SL or SCL was detected based on the number of photons. Though this method is effective, it could not identify the sonochemical zones of an ultrasonic systems. SL/SCL images, on the other hand, enable identification of 'active' sonochemical zones. However, these images often provide just qualitative data as the harvesting of light intensity data from the images is tedious and require high resolution images. In this work, we propose a new image analysis technique using pseudo-colouring images to quantify the SCL zones based on the intensities of the SCL images and followed by comparison of the active SCL zones with COMSOL simulated acoustic pressure zones. Copyright © 2016 Elsevier B.V. All rights reserved.

Diagnostic value of three-dimensional magnetic resonance imaging of inner ear after intratympanic gadolinium injection, and clinical application of magnetic resonance imaging scoring system in patients with delayed endolymphatic hydrops.

PubMed

Gu, X; Fang, Z-M; Liu, Y; Lin, S-L; Han, B; Zhang, R; Chen, X

2014-01-01

Three-dimensional fluid-attenuated inversion recovery magnetic resonance imaging of the inner ear after intratympanic injection of gadolinium, together with magnetic resonance imaging scoring of the perilymphatic space, were used to investigate the positive identification rate of hydrops and determine the technique's diagnostic value for delayed endolymphatic hydrops. Twenty-five patients with delayed endolymphatic hydrops underwent pure tone audiometry, bithermal caloric testing, vestibular-evoked myogenic potential testing and three-dimensional magnetic resonance imaging of the inner ear after bilateral intratympanic injection of gadolinium. The perilymphatic space of the scanned images was analysed to investigate the positive identification rate of endolymphatic hydrops. According to the magnetic resonance imaging scoring of the perilymphatic space and the diagnostic standard, 84 per cent of the patients examined had endolymphatic hydrops. In comparison, the positive identification rates for vestibular-evoked myogenic potential and bithermal caloric testing were 52 per cent and 72 per cent respectively. Three-dimensional magnetic resonance imaging after intratympanic injection of gadolinium is valuable in the diagnosis of delayed endolymphatic hydrops and its classification. The perilymphatic space scoring system improved the diagnostic accuracy of magnetic resonance imaging.

Dental x-ray image segmentation

NASA Astrophysics Data System (ADS)

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.

Reliability of landmark identification in cephalometric radiography acquired by a storage phosphor imaging system.

PubMed

Chen, Y-J; Chen, S-K; Huang, H-W; Yao, C-C; Chang, H-F

2004-09-01

To compare the cephalometric landmark identification on softcopy and hardcopy of direct digital cephalography acquired by a storage-phosphor (SP) imaging system. Ten digital cephalograms and their conventional counterpart, hardcopy on a transparent blue film, were obtained by a SP imaging system and a dye sublimation printer. Twelve orthodontic residents identified 19 cephalometric landmarks on monitor-displayed SP digital images with computer-aided method and on their hardcopies with conventional method. The x- and y-coordinates for each landmark, indicating the horizontal and vertical positions, were analysed to assess the reliability of landmark identification and evaluate the concordance of the landmark locations in softcopy and hardcopy of SP digital cephalometric radiography. For each of the 19 landmarks, the location differences as well as the horizontal and vertical components were statistically significant between SP digital cephalometric radiography and its hardcopy. Smaller interobserver errors on SP digital images than those on their hardcopies were noted for all the landmarks, except point Go in vertical direction. The scatter-plots demonstrate the characteristic distribution of the interobserver error in both horizontal and vertical directions. Generally, the dispersion of interobserver error on SP digital cephalometric radiography is less than that on its hardcopy with conventional method. The SP digital cephalometric radiography could yield better or comparable level of performance in landmark identification as its hardcopy, except point Go in vertical direction.

Results of ACTIM: an EDA study on spectral laser imaging

NASA Astrophysics Data System (ADS)

Hamoir, Dominique; Hespel, Laurent; Déliot, Philippe; Boucher, Yannick; Steinvall, Ove; Ahlberg, Jörgen; Larsson, Hakan; Letalick, Dietmar; Lutzmann, Peter; Repasi, Endre; Ritt, Gunnar

2011-11-01

The European Defence Agency (EDA) launched the Active Imaging (ACTIM) study to investigate the potential of active imaging, especially that of spectral laser imaging. The work included a literature survey, the identification of promising military applications, system analyses, a roadmap and recommendations. Passive multi- and hyper-spectral imaging allows discriminating between materials. But the measured radiance in the sensor is difficult to relate to spectral reflectance due to the dependence on e.g. solar angle, clouds, shadows... In turn, active spectral imaging offers a complete control of the illumination, thus eliminating these effects. In addition it allows observing details at long ranges, seeing through degraded atmospheric conditions, penetrating obscurants (foliage, camouflage...) or retrieving polarization information. When 3D, it is suited to producing numerical terrain models and to performing geometry-based identification. Hence fusing the knowledge of ladar and passive spectral imaging will result in new capabilities. We have identified three main application areas for active imaging, and for spectral active imaging in particular: (1) long range observation for identification, (2) mid-range mapping for reconnaissance, (3) shorter range perception for threat detection. We present the system analyses that have been performed for confirming the interests, limitations and requirements of spectral active imaging in these three prioritized applications.

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

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.

Optical/digital identification/verification system based on digital watermarking technology

NASA Astrophysics Data System (ADS)

Herrigel, Alexander; Voloshynovskiy, Sviatoslav V.; Hrytskiv, Zenon D.

2000-06-01

This paper presents a new approach for the secure integrity verification of driver licenses, passports or other analogue identification documents. The system embeds (detects) the reference number of the identification document with the DCT watermark technology in (from) the owner photo of the identification document holder. During verification the reference number is extracted and compared with the reference number printed in the identification document. The approach combines optical and digital image processing techniques. The detection system must be able to scan an analogue driver license or passport, convert the image of this document into a digital representation and then apply the watermark verification algorithm to check the payload of the embedded watermark. If the payload of the watermark is identical with the printed visual reference number of the issuer, the verification was successful and the passport or driver license has not been modified. This approach constitutes a new class of application for the watermark technology, which was originally targeted for the copyright protection of digital multimedia data. The presented approach substantially increases the security of the analogue identification documents applied in many European countries.

Applying face identification to detecting hijacking of airplane

NASA Astrophysics Data System (ADS)

Luo, Xuanwen; Cheng, Qiang

2004-09-01

That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

Ballistics projectile image analysis for firearm identification.

PubMed

Li, Dongguang

2006-10-01

This paper is based upon the observation that, when a bullet is fired, it creates characteristic markings on the cartridge case and projectile. From these markings, over 30 different features can be distinguished, which, in combination, produce a "fingerprint" for a firearm. By analyzing features within such a set of firearm fingerprints, it will be possible to identify not only the type and model of a firearm, but also each and every individual weapon just as effectively as human fingerprint identification. A new analytic system based on the fast Fourier transform for identifying projectile specimens by the line-scan imaging technique is proposed in this paper. This paper develops optical, photonic, and mechanical techniques to map the topography of the surfaces of forensic projectiles for the purpose of identification. Experiments discussed in this paper are performed on images acquired from 16 various weapons. Experimental results show that the proposed system can be used for firearm identification efficiently and precisely through digitizing and analyzing the fired projectiles specimens.

Real-time color image processing for forensic fiber investigations

NASA Astrophysics Data System (ADS)

Paulsson, Nils

1995-09-01

This paper describes a system for automatic fiber debris detection based on color identification. The properties of the system are fast analysis and high selectivity, a necessity when analyzing forensic fiber samples. An ordinary investigation separates the material into well above 100,000 video images to analyze. The system is based on standard techniques such as CCD-camera, motorized sample table, and IBM-compatible PC/AT with add-on-boards for video frame digitalization and stepping motor control as the main parts. It is possible to operate the instrument at full video rate (25 image/s) with aid of the HSI-color system (hue- saturation-intensity) and software optimization. High selectivity is achieved by separating the analysis into several steps. The first step is fast direct color identification of objects in the analyzed video images and the second step analyzes detected objects with a more complex and time consuming stage of the investigation to identify single fiber fragments for subsequent analysis with more selective techniques.

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

PubMed

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.

Automatic measurement of images on astrometric plates

NASA Astrophysics Data System (ADS)

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).

Evaluation and implementation of a machine vision system to categorize extraneous matter in cotton

USDA-ARS?s Scientific Manuscript database

The Cotton Trash Identification System (CTIS) developed at the Southwestern Cotton Ginning Research Laboratory was evaluated for identification and categorization of extraneous matter (EM) in cotton. The system’s categorization of trash objects in cotton images was evaluated against Agricultural Mar...

Experiment research on infrared targets signature in mid and long IR spectral bands

NASA Astrophysics Data System (ADS)

Wang, Chensheng; Hong, Pu; Lei, Bo; Yue, Song; Zhang, Zhijie; Ren, Tingting

2013-09-01

Since the infrared imaging system has played a significant role in the military self-defense system and fire control system, the radiation signature of IR target becomes an important topic in IR imaging application technology. IR target signature can be applied in target identification, especially for small and dim targets, as well as the target IR thermal design. To research and analyze the targets IR signature systematically, a practical and experimental project is processed under different backgrounds and conditions. An infrared radiation acquisition system based on a MWIR cooled thermal imager and a LWIR cooled thermal imager is developed to capture the digital infrared images. Furthermore, some instruments are introduced to provide other parameters. According to the original image data and the related parameters in a certain scene, the IR signature of interested target scene can be calculated. Different background and targets are measured with this approach, and a comparison experiment analysis shall be presented in this paper as an example. This practical experiment has proved the validation of this research work, and it is useful in detection performance evaluation and further target identification research.

Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies.

PubMed

Kushida, Clete A; Nichols, Deborah A; Jadrnicek, Rik; Miller, Ric; Walsh, James K; Griffin, Kara

2012-07-01

De-identification and anonymization are strategies that are used to remove patient identifiers in electronic health record data. The use of these strategies in multicenter research studies is paramount in importance, given the need to share electronic health record data across multiple environments and institutions while safeguarding patient privacy. Systematic literature search using keywords of de-identify, deidentify, de-identification, deidentification, anonymize, anonymization, data scrubbing, and text scrubbing. Search was conducted up to June 30, 2011 and involved 6 different common literature databases. A total of 1798 prospective citations were identified, and 94 full-text articles met the criteria for review and the corresponding articles were obtained. Search results were supplemented by review of 26 additional full-text articles; a total of 120 full-text articles were reviewed. A final sample of 45 articles met inclusion criteria for review and discussion. Articles were grouped into text, images, and biological sample categories. For text-based strategies, the approaches were segregated into heuristic, lexical, and pattern-based systems versus statistical learning-based systems. For images, approaches that de-identified photographic facial images and magnetic resonance image data were described. For biological samples, approaches that managed the identifiers linked with these samples were discussed, particularly with respect to meeting the anonymization requirements needed for Institutional Review Board exemption under the Common Rule. Current de-identification strategies have their limitations, and statistical learning-based systems have distinct advantages over other approaches for the de-identification of free text. True anonymization is challenging, and further work is needed in the areas of de-identification of datasets and protection of genetic information.

Can active proton interrogation find shielded nuclear threats at human-safe radiation levels?

NASA Astrophysics Data System (ADS)

Liew, Seth Van

2017-05-01

A new method of low-dose proton radiography is presented. The system is composed of an 800 MeV proton source, bending magnets, and compact detectors, and is designed for drive-through cargo scanning. The system has been simulated using GEANT4. Material identification algorithms and pixel sorting methods are presented that allow the system to perform imaging at doses low enough to scan passenger vehicles and people. Results are presented on imaging efficacy of various materials and cluttered cargoes. The identification of shielded nuclear materials at human-safe doses has been demonstrated.

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

PubMed

Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

2017-09-07

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

EOID Evaluation and Automated Target Recognition

DTIC Science & Technology

2002-09-30

Electro - Optic IDentification (EOID) sensors into shallow water littoral zone minehunting systems on towed, remotely operated, and autonomous platforms. These downlooking laser-based sensors operate at unparalleled standoff ranges in visible wavelengths to image and identify mine-like objects (MLOs) that have been detected through other sensing means such as magnetic induction and various modes of acoustic imaging. Our long term goal is to provide a robust automated target cueing and identification capability for use with these imaging sensors. It is also our goal to assist

EOID Evaluation and Automated Target Recognition

DTIC Science & Technology

2001-09-30

Electro - Optic IDentification (EOID) sensors into shallow water littoral zone minehunting systems on towed, remotely operated, and autonomous platforms. These downlooking laser-based sensors operate at unparalleled standoff ranges in visible wavelengths to image and identify mine-like objects that have been detected through other sensing means such as magnetic induction and various modes of acoustic imaging. Our long term goal is to provide a robust automated target cueing and identification capability for use with these imaging sensors. It is also our goal to assist the

Motion estimation of subcellular structures from fluorescence microscopy images.

PubMed

Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R

2017-07-01

We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.

An online ID identification system for liquefied-gas cylinder plant

NASA Astrophysics Data System (ADS)

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.

A web-based institutional DICOM distribution system with the integration of the Clinical Trial Processor (CTP).

PubMed

Aryanto, K Y E; Broekema, A; Langenhuysen, R G A; Oudkerk, M; van Ooijen, P M A

2015-05-01

To develop and test a fast and easy rule-based web-environment with optional de-identification of imaging data to facilitate data distribution within a hospital environment. A web interface was built using Hypertext Preprocessor (PHP), an open source scripting language for web development, and Java with SQL Server to handle the database. The system allows for the selection of patient data and for de-identifying these when necessary. Using the services provided by the RSNA Clinical Trial Processor (CTP), the selected images were pushed to the appropriate services using a protocol based on the module created for the associated task. Five pipelines, each performing a different task, were set up in the server. In a 75 month period, more than 2,000,000 images are transferred and de-identified in a proper manner while 20,000,000 images are moved from one node to another without de-identification. While maintaining a high level of security and stability, the proposed system is easy to setup, it integrate well with our clinical and research practice and it provides a fast and accurate vendor-neutral process of transferring, de-identifying, and storing DICOM images. Its ability to run different de-identification processes in parallel pipelines is a major advantage in both clinical and research setting.

Page segmentation using script identification vectors: A first look

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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,more » 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.« less

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Electromagnetic image guidance in gynecology: prospective study of a new laparoscopic imaging and targeting technique for the treatment of symptomatic uterine fibroids.

PubMed

Galen, Donald I

2015-10-15

Uterine fibroids occur singly or as multiple benign tumors originating in the myometrium. Because they vary in size and location, the approach and technique for their identification and surgical management vary. Reference images, such as ultrasound images, magnetic resonance images, and sonohystograms, do not provide real-time intraoperative findings. Electromagnetic image guidance, as incorporated in the Acessa Guidance System, has been cleared by the FDA to facilitate targeting and ablation of uterine fibroids during laparoscopic surgery. This is the first feasibility study to verify the features and usefulness of the guidance system in targeting symptomatic uterine fibroids-particularly hard-to-reach intramural fibroids and those abutting the endometrium. One gynecologic surgeon, who had extensive prior experience in laparoscopic ultrasound-guided identification of fibroids, treated five women with symptomatic uterine fibroids using the Acessa Guidance System. The surgeon evaluated the system and its features in terms of responses to prescribed statements; the responses were analyzed prospectively. The surgeon strongly agreed (96 %) or agreed (4 %) with statements describing the helpfulness of the transducer and handpiece's dynamic animation in targeting each fibroid, reaching the fibroid quickly, visualizing the positions of the transducer and handpiece within the pelvic cavity, and providing the surgeon with confidence when targeting the fibroid even during "out-of-plane" positioning of the handpiece. The surgeon's positive user experience was evident in the guidance system's facilitation of accurate handpiece tip placement during targeting and ablation of uterine fibroids. Continued study of electromagnetic image guidance in the laparoscopic identification and treatment of fibroids is warranted. ClinicalTrials.gov Identifier: NCT01842789.

Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

PubMed

Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

2016-12-22

Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in extraction and selection of features will be implemented.

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

Identification of early cancerous lesion of esophagus with endoscopic images by hyperspectral image technique (Conference Presentation)

NASA Astrophysics Data System (ADS)

Huang, Shih-Wei; Chen, Shih-Hua; Chen, Weichung; Wu, I.-Chen; Wu, Ming Tsang; Kuo, Chie-Tong; Wang, Hsiang-Chen

2016-03-01

This study presents a method to identify early esophageal cancer within endoscope using hyperspectral imaging technology. The research samples are three kinds of endoscopic images including white light endoscopic, chromoendoscopic, and narrow-band endoscopic images with different stages of pathological changes (normal, dysplasia, dysplasia - esophageal cancer, and esophageal cancer). Research is divided into two parts: first, we analysis the reflectance spectra of endoscopic images with different stages to know the spectral responses by pathological changes. Second, we identified early cancerous lesion of esophagus by principal component analysis (PCA) of the reflectance spectra of endoscopic images. The results of this study show that the identification of early cancerous lesion is possible achieve from three kinds of images. In which the spectral characteristics of NBI endoscopy images of a gray area than those without the existence of the problem the first two, and the trend is very clear. Therefore, if simply to reflect differences in the degree of spectral identification, chromoendoscopic images are suitable samples. The best identification of early esophageal cancer is using the NBI endoscopic images. Based on the results, the use of hyperspectral imaging technology in the early endoscopic esophageal cancer lesion image recognition helps clinicians quickly diagnose. We hope for the future to have a relatively large amount of endoscopic image by establishing a hyperspectral imaging database system developed in this study, so the clinician can take this repository more efficiently preliminary diagnosis.

Particle image velocimetry for the Surface Tension Driven Convection Experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Particle image velocimetry for the surface tension driven convection experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Identification of handheld objects for electro-optic/FLIR applications

NASA Astrophysics Data System (ADS)

Moyer, Steve K.; Flug, Eric; Edwards, Timothy C.; Krapels, Keith A.; Scarbrough, John

2004-08-01

This paper describes research on the determination of the fifty-percent probability of identification cycle criterion (N50) for two sets of handheld objects. The first set consists of 12 objects which are commonly held in a single hand. The second set consists of 10 objects commonly held in both hands. These sets consist of not only typical civilian handheld objects but also objects that are potentially lethal. A pistol, a cell phone, a rocket propelled grenade (RPG) launcher, and a broom are examples of the objects in these sets. The discrimination of these objects is an inherent part of homeland security, force protection, and also general population security. Objects were imaged from each set in the visible and mid-wave infrared (MWIR) spectrum. Various levels of blur are then applied to these images. These blurred images were then used in a forced choice perception experiment. Results were analyzed as a function of blur level and target size to give identification probability as a function of resolvable cycles on target. These results are applicable to handheld object target acquisition estimates for visible imaging systems and MWIR systems. This research provides guidance in the design and analysis of electro-optical systems and forward-looking infrared (FLIR) systems for use in homeland security, force protection, and also general population security.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

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

PubMed

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.

Modular Spectral Imaging System for Discrimination of Pigments in Cells and Microbial Communities▿ †

PubMed Central

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

2009-01-01

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. PMID:19074609

Identification of staphylococcus species with hyperspectral microscope imaging and classification algrorithms

USDA-ARS?s Scientific Manuscript database

Hyperspectral microscope imaging is presented as a rapid and efficient tool to classify foodborne bacteria species. The spectral data were obtained from five different species of Staphylococcus spp. with a hyperspectral microscope imaging system that provided a maximum of 89 contiguous spectral imag...

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Versatile illumination platform and fast optical switch to give standard observation camera gated active imaging capacity

NASA Astrophysics Data System (ADS)

Grasser, R.; Peyronneaudi, Benjamin; Yon, Kevin; Aubry, Marie

2015-10-01

CILAS, subsidiary of Airbus Defense and Space, develops, manufactures and sales laser-based optronics equipment for defense and homeland security applications. Part of its activity is related to active systems for threat detection, recognition and identification. Active surveillance and active imaging systems are often required to achieve identification capacity in case for long range observation in adverse conditions. In order to ease the deployment of active imaging systems often complex and expensive, CILAS suggests a new concept. It consists on the association of two apparatus working together. On one side, a patented versatile laser platform enables high peak power laser illumination for long range observation. On the other side, a small camera add-on works as a fast optical switch to select photons with specific time of flight only. The association of the versatile illumination platform and the fast optical switch presents itself as an independent body, so called "flash module", giving to virtually any passive observation systems gated active imaging capacity in NIR and SWIR.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jani, S; Low, D; Lamb, J

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 weremore » 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 automatically detected using 3D setup images of two imaging modalities across three commonly-treated anatomical sites.« less

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

NASA Astrophysics Data System (ADS)

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.

Robust finger vein ROI localization based on flexible segmentation.

PubMed

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-10-24

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.

Robust Finger Vein ROI Localization Based on Flexible Segmentation

PubMed Central

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-01-01

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system. PMID:24284769

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

The effect of image alterations on identification using palmar flexion creases.

PubMed

Cook, Tom; Sutton, Raul; Buckley, Kevan

2013-11-01

Palmprints are identified using matching of minutia points, which can be time consuming for fingerprint experts and in database searches. This article analyzes the operational characteristics of a palmar flexion crease (PFC) identification software tool, using a dataset of 10 replicates of 100 palms, where the user can label and match palmar line features. Results show that 100 palmprint images modified 10 times each using rotation, translation, and additive noise, mimicking some of the characteristics found in crime scene palmar marks, can be identified with a 99.2% genuine acceptance rate and 0% false acceptance rate when labeled within 3.5 mm of the PFC. Partial palmprint images can also be identified using the same method to filter the dataset prior to traditional matching, while maintaining an effective genuine acceptance rate. The work shows that identification using PFCs can improve palmprint identification through integration with existing systems, and through dedicated palmprint identification applications. © 2013 American Academy of Forensic Sciences.

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing

PubMed Central

Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu

2017-01-01

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%. PMID:28880254

Analysis of energy dispersive x-ray diffraction profiles for material identification, imaging and system control

NASA Astrophysics Data System (ADS)

Cook, Emily Jane

2008-12-01

This thesis presents the analysis of low angle X-ray scatter measurements taken with an energy dispersive system for substance identification, imaging and system control. Diffraction measurements were made on illicit drugs, which have pseudo- crystalline structures and thus produce diffraction patterns comprising a se ries of sharp peaks. Though the diffraction profiles of each drug are visually characteristic, automated detection systems require a substance identification algorithm, and multivariate analysis was selected as suitable. The software was trained with measured diffraction data from 60 samples covering 7 illicit drugs and 5 common cutting agents, collected with a range of statistical qual ities and used to predict the content of 7 unknown samples. In all cases the constituents were identified correctly and the contents predicted to within 15%. Soft tissues exhibit broad peaks in their diffraction patterns. Diffraction data were collected from formalin fixed breast tissue samples and used to gen erate images. Maximum contrast between healthy and suspicious regions was achieved using momentum transfer windows 1.04-1.10 and 1.84-1.90 nm_1. The resulting images had an average contrast of 24.6% and 38.9% compared to the corresponding transmission X-ray images (18.3%). The data was used to simulate the feedback for an adaptive imaging system and the ratio of the aforementioned momentum transfer regions found to be an excellent pa rameter. Investigation into the effects of formalin fixation on human breast tissue and animal tissue equivalents indicated that fixation in standard 10% buffered formalin does not alter the diffraction profiles of tissue in the mo mentum transfer regions examined, though 100% unbuffered formalin affects the profile of porcine muscle tissue (a substitute for glandular and tumourous tissue), though fat is unaffected.

Detection of small surface vessels in near, medium, and far infrared spectral bands

NASA Astrophysics Data System (ADS)

Dulski, R.; Milewski, S.; Kastek, M.; Trzaskawka, P.; Szustakowski, M.; Ciurapinski, W.; Zyczkowski, M.

2011-11-01

Protection of naval bases and harbors requires close co-operation between security and access control systems covering land areas and those monitoring sea approach routes. The typical location of naval bases and harbors - usually next to a large city - makes it difficult to detect and identify a threat in the dense regular traffic of various sea vessels (i.e. merchant ships, fishing boats, tourist ships). Due to the properties of vessel control systems, such as AIS (Automatic Identification System), and the effectiveness of radar and optoelectronic systems against different targets it seems that fast motor boats called RIB (Rigid Inflatable Boat) could be the most serious threat to ships and harbor infrastructure. In the paper the process and conditions for the detection and identification of high-speed boats in the areas of ports and naval bases in the near, medium and far infrared is presented. Based on the results of measurements and recorded thermal images the actual temperature contrast delta T (RIB / sea) will be determined, which will further allow to specify the theoretical ranges of detection and identification of the RIB-type targets for an operating security system. The data will also help to determine the possible advantages of image fusion where the component images are taken in different spectral ranges. This will increase the probability of identifying the object by the multi-sensor security system equipped additionally with the appropriate algorithms for detecting, tracking and performing the fusion of images from the visible and infrared cameras.

Enhanced terahertz imaging system performance analysis and design tool for concealed weapon identification

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Franck, Charmaine C.; Espinola, Richard L.; Petkie, Douglas T.; De Lucia, Frank C.; Jacobs, Eddie L.

2011-11-01

The U.S. Army Research Laboratory (ARL) and the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) have developed a terahertz-band imaging system performance model/tool for detection and identification of concealed weaponry. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security & Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). This paper will provide a comprehensive review of an enhanced, user-friendly, Windows-executable, terahertz-band imaging system performance analysis and design tool that now includes additional features such as a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures. This newly enhanced THz imaging system design tool is an extension of the advanced THz imaging system performance model that was developed under the Defense Advanced Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. This paper will also provide example system component (active-illumination source and detector) trade-study analyses using the new features of this user-friendly THz imaging system performance analysis and design tool.

Speckle reduction during all-fiber common-path optical coherence tomography of the cavernous nerves

NASA Astrophysics Data System (ADS)

Chitchian, Shahab; Fiddy, Michael; Fried, Nathaniel M.

2009-02-01

Improvements in identification, imaging, and visualization of the cavernous nerves during prostate cancer surgery, which are responsible for erectile function, may improve nerve preservation and postoperative sexual potency. In this study, we use a rat prostate, ex vivo, to evaluate the feasibility of optical coherence tomography (OCT) as a diagnostic tool for real-time imaging and identification of the cavernous nerves. A novel OCT system based on an all single-mode fiber common-path interferometer-based scanning system is used for this purpose. A wavelet shrinkage denoising technique using Stein's unbiased risk estimator (SURE) algorithm to calculate a data-adaptive threshold is implemented for speckle noise reduction in the OCT image. The signal-to-noise ratio (SNR) was improved by 9 dB and the image quality metrics of the cavernous nerves also improved significantly.

Radar image processing of real aperture SLAR data for the detection and identification of iceberg and ship targets

NASA Technical Reports Server (NTRS)

Marthaler, J. G.; Heighway, J. E.

1979-01-01

An iceberg detection and identification system consisting of a moderate resolution Side Looking Airborne Radar (SLAR) interfaced with a Radar Image Processor (RIP) based on a ROLM 1664 computer with a 32K core memory updatable to 64K is described. The system can be operated in high- or low-resolution sampling modes. Specifically designed algorithms are applied to digitized signal returns to provide automatic target detection and location, geometrically correct video image display and data recording. The real aperture Motorola AN/APS-94D SLAR operates in the X-band and is tunable between 9.10 and 9.40 GHz; its output power is 45 kW peak with a pulse repetition rate of 750 pulses per hour. Schematic diagrams of the system are provided, together with preliminary test data.

Underwater electro-optical system for mine identification

NASA Astrophysics Data System (ADS)

Strand, Michael P.

1995-06-01

The Electro-Optic Identification (EOID) Sensors project is developing a Laser Visual Iidentification Sensor (LVIS) for identification of proud, partially buried, and moored mines in shallow water/very shallow water. LVIS will be deployed in small diameter underwater vehicles, including unmanned underwater vehicles (UUVs). Since the mission is mine identification, LVIS must: a) deliver high quality images in turbid coastal waters, while b) being compatible with the size and power constraints imposed by the intended deployment platforms. This project is sponsored by the Office of Naval Research, as a part of the AOA Mine Reconnaissance/Hunter program. High quality images which retain target detail and contrast are required for mine identification. LVIS will be designed to produce images of minelike contacts (MLC) of sufficient quality to allow identification while operating in turbid coastal waters from a small diameter UUV. Technology goals for the first generation LVIS are a) identification range up to 40 feet for proud, partially buried, and moored MLCs under coastal water conditions; b) day/night operation from a UUV operating at speeds up to 4 knots; c) power consumption less than 500 watts, with 275 watts being typical; and d) packaged within a 32-inch long portion of a 21-inch diameter vehicle section.

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

PubMed

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.

Interventional multispectral photoacoustic imaging with a clinical linear array ultrasound probe for guiding nerve blocks

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; West, Simeon J.; Nikitichev, Daniil I.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2016-03-01

Accurate identification of tissue structures such as nerves and blood vessels is critically important for interventional procedures such as nerve blocks. Ultrasound imaging is widely used as a guidance modality to visualize anatomical structures in real-time. However, identification of nerves and small blood vessels can be very challenging, and accidental intra-neural or intra-vascular injections can result in significant complications. Multi-spectral photoacoustic imaging can provide high sensitivity and specificity for discriminating hemoglobin- and lipid-rich tissues. However, conventional surface-illumination-based photoacoustic systems suffer from limited sensitivity at large depths. In this study, for the first time, an interventional multispectral photoacoustic imaging (IMPA) system was used to image nerves in a swine model in vivo. Pulsed excitation light with wavelengths in the ranges of 750 - 900 nm and 1150 - 1300 nm was delivered inside the body through an optical fiber positioned within the cannula of an injection needle. Ultrasound waves were received at the tissue surface using a clinical linear array imaging probe. Co-registered B-mode ultrasound images were acquired using the same imaging probe. Nerve identification was performed using a combination of B-mode ultrasound imaging and electrical stimulation. Using a linear model, spectral-unmixing of the photoacoustic data was performed to provide image contrast for oxygenated and de-oxygenated hemoglobin, water and lipids. Good correspondence between a known nerve location and a lipid-rich region in the photoacoustic images was observed. The results indicate that IMPA is a promising modality for guiding nerve blocks and other interventional procedures. Challenges involved with clinical translation are discussed.

Identification of uncommon objects in containers

DOEpatents

Bremer, Peer-Timo; Kim, Hyojin; Thiagarajan, Jayaraman J.

2017-09-12

A system for identifying in an image an object that is commonly found in a collection of images and for identifying a portion of an image that represents an object based on a consensus analysis of segmentations of the image. The system collects images of containers that contain objects for generating a collection of common objects within the containers. To process the images, the system generates a segmentation of each image. The image analysis system may also generate multiple segmentations for each image by introducing variations in the selection of voxels to be merged into a segment. The system then generates clusters of the segments based on similarity among the segments. Each cluster represents a common object found in the containers. Once the clustering is complete, the system may be used to identify common objects in images of new containers based on similarity between segments of images and the clusters.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitus, B.R.; Goddard, J.S.; Jatko, W.B.

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)more » 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.« less

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

PubMed

Li, Junfeng; Wan, Xiaoxia

2018-01-15

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. Copyright © 2017 Elsevier B.V. All rights reserved.

Fusion of imaging and nonimaging data for surveillance aircraft

NASA Astrophysics Data System (ADS)

Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

1997-06-01

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).

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

PubMed

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 Elsevier Inc. All rights reserved.

Development of a 3-D Defocusing Liquid Crystal Particle Thermometry and Velocimetry (3DDLCPTV) System

DTIC Science & Technology

2007-05-01

general, off axis imaging can cause distortion and astigmatism in the image if proper precautions are not taken. In this case, the lens selection... astigmatism into the optical system. This astigmatism takes the form of a blurring in each image directed away from the optical axis. This blurring...is non-trivial and makes particle identification nearly impossible. Images of particles from two of the off axis cameras with the astigmatism present

FIZICS: fluorescent imaging zone identification system, a novel macro imaging system.

PubMed

Skwish, Stephen; Asensio, Francisco; King, Greg; Clarke, Glenn; Kath, Gary; Salvatore, Michael J; Dufresne, Claude

2004-12-01

Constantly improving biological assay development continues to drive technological requirements. Recently, a specification was defined for capturing white light and fluorescent images of agar plates ranging in size from the NUNC Omni tray (96-well footprint, 128 x 85 mm) to the NUNC Bio Assay Dish (245 x 245 mm). An evaluation of commercially available products failed to identify any system capable of fluorescent macroimaging with discrete wavelength selection. To address the lack of a commercially available system, a custom imaging system was designed and constructed. This system provides the same capabilities of many commercially available systems with the added ability to fluorescently image up to a 245 x 245 mm area using wavelengths in the visible light spectrum.

Estimating False Positive Contamination in Crater Annotations from Citizen Science Data

NASA Astrophysics Data System (ADS)

Tar, P. D.; Bugiolacchi, R.; Thacker, N. A.; Gilmour, J. D.

2017-01-01

Web-based citizen science often involves the classification of image features by large numbers of minimally trained volunteers, such as the identification of lunar impact craters under the Moon Zoo project. Whilst such approaches facilitate the analysis of large image data sets, the inexperience of users and ambiguity in image content can lead to contamination from false positive identifications. We give an approach, using Linear Poisson Models and image template matching, that can quantify levels of false positive contamination in citizen science Moon Zoo crater annotations. Linear Poisson Models are a form of machine learning which supports predictive error modelling and goodness-of-fits, unlike most alternative machine learning methods. The proposed supervised learning system can reduce the variability in crater counts whilst providing predictive error assessments of estimated quantities of remaining true verses false annotations. In an area of research influenced by human subjectivity, the proposed method provides a level of objectivity through the utilisation of image evidence, guided by candidate crater identifications.

Image change detection systems, methods, and articles of manufacture

DOEpatents

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.

Improvement of single wavelength-based Thai jasmine rice identification with elliptic Fourier descriptor and neural network analysis

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2012-11-01

Instead of considering only the amount of fluorescent signal spatially distributed on the image of milled rice grains this paper shows how our single-wavelength spectral-imaging-based Thai jasmine (KDML105) rice identification system can be improved by analyzing the shape and size of the image of each milled rice variety especially during the image threshold operation. The image of each milled rice variety is expressed as chain codes and elliptic Fourier coefficients. After that, a feed-forward back-propagation neural network model is applied, resulting in an improved average FAR of 11.0% and FRR of 19.0% in identifying KDML105 milled rice from the unwanted four milled rice varieties.

Astrometrica: Astrometric data reduction of CCD images

NASA Astrophysics Data System (ADS)

Raab, Herbert

2012-03-01

Astrometrica is an interactive software tool for scientific grade astrometric data reduction of CCD images. The current version of the software is for the Windows 32bit operating system family. Astrometrica reads FITS (8, 16 and 32 bit integer files) and SBIG image files. The size of the images is limited only by available memory. It also offers automatic image calibration (Dark Frame and Flat Field correction), automatic reference star identification, automatic moving object detection and identification, and access to new-generation star catalogs (PPMXL, UCAC 3 and CMC-14), in addition to online help and other features. Astrometrica is shareware, available for use for a limited period of time (100 days) for free; special arrangements can be made for educational projects.

FBI Fingerprint Image Capture System High-Speed-Front-End throughput modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rathke, P.M.

1993-09-01

The Federal Bureau of Investigation (FBI) has undertaken a major modernization effort called the Integrated Automated Fingerprint Identification System (IAFISS). This system will provide centralized identification services using automated fingerprint, subject descriptor, mugshot, and document processing. A high-speed Fingerprint Image Capture System (FICS) is under development as part of the IAFIS program. The FICS will capture digital and microfilm images of FBI fingerprint cards for input into a central database. One FICS design supports two front-end scanning subsystems, known as the High-Speed-Front-End (HSFE) and Low-Speed-Front-End, to supply image data to a common data processing subsystem. The production rate of themore » HSFE is critical to meeting the FBI`s fingerprint card processing schedule. A model of the HSFE has been developed to help identify the issues driving the production rate, assist in the development of component specifications, and guide the evolution of an operations plan. A description of the model development is given, the assumptions are presented, and some HSFE throughput analysis is performed.« less

Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology

PubMed Central

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. PMID:22736996

Feasibility study on a portable field pest classification system design based on DSP and 3G wireless communication technology.

PubMed

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests' pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture.

A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

PubMed Central

Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

2012-01-01

Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l1 -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

Category identification of changed land-use polygons in an integrated image processing/geographic information system

NASA Technical Reports Server (NTRS)

Westmoreland, Sally; Stow, Douglas A.

1992-01-01

A framework is proposed for analyzing ancillary data and developing procedures for incorporating ancillary data to aid interactive identification of land-use categories in land-use updates. The procedures were developed for use within an integrated image processsing/geographic information systems (GIS) that permits simultaneous display of digital image data with the vector land-use data to be updated. With such systems and procedures, automated techniques are integrated with visual-based manual interpretation to exploit the capabilities of both. The procedural framework developed was applied as part of a case study to update a portion of the land-use layer in a regional scale GIS. About 75 percent of the area in the study site that experienced a change in land use was correctly labeled into 19 categories using the combination of automated and visual interpretation procedures developed in the study.

Image processing tool for automatic feature recognition and quantification

DOEpatents

Chen, Xing; Stoddard, Ryan J.

2017-05-02

A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.

The identification of living persons on images: A literature review.

PubMed

Gibelli, D; Obertová, Z; Ritz-Timme, S; Gabriel, P; Arent, T; Ratnayake, M; De Angelis, D; Cattaneo, C

2016-03-01

Personal identification in the forensic context commonly concerns unknown decedents. However, recently there has been an increase in cases which require identification of living persons, especially from surveillance systems. These cases bring about a relatively new challenge for forensic anthropologists and pathologists concerning the selection of the most suitable methodological approaches with regard to the limitations of the photographic representation of a given person for individualization and identity. Facial features are instinctively the primary focus for identification approaches. However, other body parts (e.g. hands), and body height and gait (on videos) have been considered in cases of personal identification. This review aims at summarizing the state-of-the-art concerning the identification of the living on images and videos, including a critical evaluation of the advantages and limitations of different methods. Recommendations are given in order to aid forensic practitioners who face cases of identification of living persons. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimized design of embedded DSP system hardware supporting complex algorithms

NASA Astrophysics Data System (ADS)

Li, Yanhua; Wang, Xiangjun; Zhou, Xinling

2003-09-01

The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.

Data Citation in Neuroimaging: Proposed Best Practices for Data Identification and Attribution

PubMed Central

Honor, Leah B.; Haselgrove, Christian; Frazier, Jean A.; Kennedy, David N.

2016-01-01

Data sharing and reuse, while widely accepted as good ideas, have been slow to catch on in any concrete and consistent way. One major hurdle within the scientific community has been the lack of widely accepted standards for citing that data, making it difficult to track usage and measure impact. Within the neuroimaging community, there is a need for a way to not only clearly identify and cite datasets, but also to derive new aggregate sets from multiple sources while clearly maintaining lines of attribution. This work presents a functional prototype of a system to integrate Digital Object Identifiers (DOI) and a standardized metadata schema into a XNAT-based repository workflow, allowing for identification of data at both the project and image level. These item and source level identifiers allow any newly defined combination of images, from any number of projects, to be tagged with a new group-level DOI that automatically inherits the individual attributes and provenance information of its constituent parts. This system enables the tracking of data reuse down to the level of individual images. The implementation of this type of data identification system would impact researchers and data creators, data hosting facilities, and data publishers, but the benefit of having widely accepted standards for data identification and attribution would go far toward making data citation practical and advantageous. PMID:27570508

Data Citation in Neuroimaging: Proposed Best Practices for Data Identification and Attribution.

PubMed

Honor, Leah B; Haselgrove, Christian; Frazier, Jean A; Kennedy, David N

2016-01-01

Data sharing and reuse, while widely accepted as good ideas, have been slow to catch on in any concrete and consistent way. One major hurdle within the scientific community has been the lack of widely accepted standards for citing that data, making it difficult to track usage and measure impact. Within the neuroimaging community, there is a need for a way to not only clearly identify and cite datasets, but also to derive new aggregate sets from multiple sources while clearly maintaining lines of attribution. This work presents a functional prototype of a system to integrate Digital Object Identifiers (DOI) and a standardized metadata schema into a XNAT-based repository workflow, allowing for identification of data at both the project and image level. These item and source level identifiers allow any newly defined combination of images, from any number of projects, to be tagged with a new group-level DOI that automatically inherits the individual attributes and provenance information of its constituent parts. This system enables the tracking of data reuse down to the level of individual images. The implementation of this type of data identification system would impact researchers and data creators, data hosting facilities, and data publishers, but the benefit of having widely accepted standards for data identification and attribution would go far toward making data citation practical and advantageous.

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

PubMed

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.

Implementation of Enterprise Imaging Strategy at a Chinese Tertiary Hospital.

PubMed

Li, Shanshan; Liu, Yao; Yuan, Yifang; Li, Jia; Wei, Lan; Wang, Yuelong; Fei, Xiaolu

2018-01-04

Medical images have become increasingly important in clinical practice and medical research, and the need to manage images at the hospital level has become urgent in China. To unify patient identification in examinations from different medical specialties, increase convenient access to medical images under authentication, and make medical images suitable for further artificial intelligence investigations, we implemented an enterprise imaging strategy by adopting an image integration platform as the main tool at Xuanwu Hospital. Workflow re-engineering and business system transformation was also performed to ensure the quality and content of the imaging data. More than 54 million medical images and approximately 1 million medical reports were integrated, and uniform patient identification, images, and report integration were made available to the medical staff and were accessible via a mobile application, which were achieved by implementing the enterprise imaging strategy. However, to integrate all medical images of different specialties at a hospital and ensure that the images and reports are qualified for data mining, some further policy and management measures are still needed.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia.

PubMed

Diamond, James; Anderson, Neil H; Bartels, Peter H; Montironi, Rodolfo; Hamilton, Peter W

2004-09-01

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at x 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 x 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Missing data reconstruction using Gaussian mixture models for fingerprint images

NASA Astrophysics Data System (ADS)

Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

2016-05-01

Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

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

PubMed

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.

Embedded mobile farm robot for identification of diseased plants

NASA Astrophysics Data System (ADS)

Sadistap, S. S.; Botre, B. A.; Pandit, Harshavardhan; Chandrasekhar; Rao, Adesh

2013-07-01

This paper presents the development of a mobile robot used in farms for identification of diseased plants. It puts forth two of the major aspects of robotics namely automated navigation and image processing. The robot navigates on the basis of the GPS (Global Positioning System) location and data obtained from IR (Infrared) sensors to avoid any obstacles in its path. It uses an image processing algorithm to differentiate between diseased and non-diseased plants. A robotic platform consisting of an ARM9 processor, motor drivers, robot mechanical assembly, camera and infrared sensors has been used. Mini2440 microcontroller has been used wherein Embedded linux OS (Operating System) is implemented.

Space-based infrared sensors of space target imaging effect analysis

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Classification of Suncus murinus species complex (Soricidae: Crocidurinae) in Peninsular Malaysia using image analysis and machine learning approaches.

PubMed

Abu, Arpah; Leow, Lee Kien; Ramli, Rosli; Omar, Hasmahzaiti

2016-12-22

Taxonomists frequently identify specimen from various populations based on the morphological characteristics and molecular data. This study looks into another invasive process in identification of house shrew (Suncus murinus) using image analysis and machine learning approaches. Thus, an automated identification system is developed to assist and simplify this task. In this study, seven descriptors namely area, convex area, major axis length, minor axis length, perimeter, equivalent diameter and extent which are based on the shape are used as features to represent digital image of skull that consists of dorsal, lateral and jaw views for each specimen. An Artificial Neural Network (ANN) is used as classifier to classify the skulls of S. murinus based on region (northern and southern populations of Peninsular Malaysia) and sex (adult male and female). Thus, specimen classification using Training data set and identification using Testing data set were performed through two stages of ANNs. At present, the classifier used has achieved an accuracy of 100% based on skulls' views. Classification and identification to regions and sexes have also attained 72.5%, 87.5% and 80.0% of accuracy for dorsal, lateral, and jaw views, respectively. This results show that the shape characteristic features used are substantial because they can differentiate the specimens based on regions and sexes up to the accuracy of 80% and above. Finally, an application was developed and can be used for the scientific community. This automated system demonstrates the practicability of using computer-assisted systems in providing interesting alternative approach for quick and easy identification of unknown species.

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.

PubMed

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 (p<0.05). Image qualities of low-dose CTs deteriorated significantly when tube current was set at 100mA or less by using detector 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 (p<0.05). Detector collimation and beam pitch were important factors for the image quality and identification of GGA and nodules by 16- and 64-detector row CT.

Intelligent person identification system using stereo camera-based height and stride estimation

NASA Astrophysics Data System (ADS)

Ko, Jung-Hwan; Jang, Jae-Hun; Kim, Eun-Soo

2005-05-01

In this paper, a stereo camera-based intelligent person identification system is suggested. In the proposed method, face area of the moving target person is extracted from the left image of the input steros image pair by using a threshold value of YCbCr color model and by carrying out correlation between the face area segmented from this threshold value of YCbCr color model and the right input image, the location coordinates of the target face can be acquired, and then these values are used to control the pan/tilt system through the modified PID-based recursive controller. Also, by using the geometric parameters between the target face and the stereo camera system, the vertical distance between the target and stereo camera system can be calculated through a triangulation method. Using this calculated vertical distance and the angles of the pan and tilt, the target's real position data in the world space can be acquired and from them its height and stride values can be finally extracted. Some experiments with video images for 16 moving persons show that a person could be identified with these extracted height and stride parameters.

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

PubMed

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.

Phantom feet on digital radionuclide images and other scary computer tales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freitas, J.E.; Dworkin, H.J.; Dees, S.M.

1989-09-01

Malfunction of a computer-assisted digital gamma camera is reported. Despite what appeared to be adequate acceptance testing, an error in the system gave rise to switching of images and identification text. A suggestion is made for using a hot marker, which would avoid the potential error of misinterpretation of patient images.

Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

NASA Astrophysics Data System (ADS)

Sánchez, Clara I.; Niemeijer, Meindert; Kockelkorn, Thessa; Abràmoff, Michael D.; van Ginneken, Bram

2009-02-01

Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.

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

NASA Astrophysics Data System (ADS)

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.

Automatic identification of the reference system based on the fourth ventricular landmarks in T1-weighted MR images.

PubMed

Fu, Yili; Gao, Wenpeng; Chen, Xiaoguang; Zhu, Minwei; Shen, Weigao; Wang, Shuguo

2010-01-01

The reference system based on the fourth ventricular landmarks (including the fastigial point and ventricular floor plane) is used in medical image analysis of the brain stem. The objective of this study was to develop a rapid, robust, and accurate method for the automatic identification of this reference system on T1-weighted magnetic resonance images. The fully automated method developed in this study consisted of four stages: preprocessing of the data set, expectation-maximization algorithm-based extraction of the fourth ventricle in the region of interest, a coarse-to-fine strategy for identifying the fastigial point, and localization of the base point. The method was evaluated on 27 Brain Web data sets qualitatively and 18 Internet Brain Segmentation Repository data sets and 30 clinical scans quantitatively. The results of qualitative evaluation indicated that the method was robust to rotation, landmark variation, noise, and inhomogeneity. The results of quantitative evaluation indicated that the method was able to identify the reference system with an accuracy of 0.7 +/- 0.2 mm for the fastigial point and 1.1 +/- 0.3 mm for the base point. It took <6 seconds for the method to identify the related landmarks on a personal computer with an Intel Core 2 6300 processor and 2 GB of random-access memory. The proposed method for the automatic identification of the reference system based on the fourth ventricular landmarks was shown to be rapid, robust, and accurate. The method has potentially utility in image registration and computer-aided surgery.

Vision Algorithm for the Solar Aspect System of the HEROES Mission

NASA Technical Reports Server (NTRS)

Cramer, Alexander

2014-01-01

This work covers the design and test of a machine vision algorithm for generating high-accuracy pitch and yaw pointing solutions relative to the sun for the High Energy Replicated Optics to Explore the Sun (HEROES) mission. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small fiducial markers. Images of this plate were processed in real time to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an "Average Intersection" method, fiducial detection by a matched filter approach, identification with an ad-hoc method based on the spacing between fiducials, and image registration with a simple least squares fit. Performance is verified on a combination of artificially generated images, test data recorded on the ground, and images from the 2013 flight

Vision Algorithm for the Solar Aspect System of the HEROES Mission

NASA Technical Reports Server (NTRS)

Cramer, Alexander; Christe, Steven; Shih, Albert

2014-01-01

This work covers the design and test of a machine vision algorithm for generating high-accuracy pitch and yaw pointing solutions relative to the sun for the High Energy Replicated Optics to Explore the Sun (HEROES) mission. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small fiducial markers. Images of this plate were processed in real time to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an Average Intersection method, fiducial detection by a matched filter approach, identification with an ad-hoc method based on the spacing between fiducials, and image registration with a simple least squares fit. Performance is verified on a combination of artificially generated images, test data recorded on the ground, and images from the 2013 flight.

Optimisation of fluorescence guidance during robot-assisted laparoscopic sentinel node biopsy for prostate cancer.

PubMed

KleinJan, Gijs H; van den Berg, Nynke S; Brouwer, Oscar R; de Jong, Jeroen; Acar, Cenk; Wit, Esther M; Vegt, Erik; van der Noort, Vincent; Valdés Olmos, Renato A; van Leeuwen, Fijs W B; van der Poel, Henk G

2014-12-01

The hybrid tracer was introduced to complement intraoperative radiotracing towards the sentinel nodes (SNs) with fluorescence guidance. Improve in vivo fluorescence-based SN identification for prostate cancer by optimising hybrid tracer preparation, injection technique, and fluorescence imaging hardware. Forty patients with a Briganti nomogram-based risk >10% of lymph node (LN) metastases were included. After intraprostatic tracer injection, SN mapping was performed (lymphoscintigraphy and single-photon emission computed tomography with computed tomography (SPECT-CT)). In groups 1 and 2, SNs were pursued intraoperatively using a laparoscopic gamma probe followed by fluorescence imaging (FI). In group 3, SNs were initially located via FI. Compared with group 1, in groups 2 and 3, a new tracer formulation was introduced that had a reduced total injected volume (2.0 ml vs. 3.2 ml) but increased particle concentration. For groups 1 and 2, the Tricam SLII with D-Light C laparoscopic FI (LFI) system was used. In group 3, the LFI system was upgraded to an Image 1 HUB HD with D-Light P system. Hybrid tracer-based SN biopsy, extended pelvic lymph node dissection, and robot-assisted radical prostatectomy. Number and location of the preoperatively identified SNs, in vivo fluorescence-based SN identification rate, tumour status of SNs and LNs, postoperative complications, and biochemical recurrence (BCR). Mean fluorescence-based SN identification improved from 63.7% (group 1) to 85.2% and 93.5% for groups 2 and 3, respectively (p=0.012). No differences in postoperative complications were found. BCR occurred in three pN0 patients. Stepwise optimisation of the hybrid tracer formulation and the LFI system led to a significant improvement in fluorescence-assisted SN identification. Preoperative SPECT-CT remained essential for guiding intraoperative SN localisation. Intraoperative fluorescence-based SN visualisation can be improved by enhancing the hybrid tracer formulation and laparoscopic fluorescence imaging system. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Study on road sign recognition in LabVIEW

NASA Astrophysics Data System (ADS)

Panoiu, M.; Rat, C. L.; Panoiu, C.

2016-02-01

Road and traffic sign identification is a field of study that can be used to aid the development of in-car advisory systems. It uses computer vision and artificial intelligence to extract the road signs from outdoor images acquired by a camera in uncontrolled lighting conditions where they may be occluded by other objects, or may suffer from problems such as color fading, disorientation, variations in shape and size, etc. An automatic means of identifying traffic signs, in these conditions, can make a significant contribution to develop an Intelligent Transport Systems (ITS) that continuously monitors the driver, the vehicle, and the road. Road and traffic signs are characterized by a number of features which make them recognizable from the environment. Road signs are located in standard positions and have standard shapes, standard colors, and known pictograms. These characteristics make them suitable for image identification. Traffic sign identification covers two problems: traffic sign detection and traffic sign recognition. Traffic sign detection is meant for the accurate localization of traffic signs in the image space, while traffic sign recognition handles the labeling of such detections into specific traffic sign types or subcategories [1].

Semi-automated identification of leopard frogs

USGS Publications Warehouse

Petrovska-Delacrétaz, Dijana; Edwards, Aaron; Chiasson, John; Chollet, Gérard; Pilliod, David S.

2014-01-01

Principal component analysis is used to implement a semi-automatic recognition system to identify recaptured northern leopard frogs (Lithobates pipiens). Results of both open set and closed set experiments are given. The presented algorithm is shown to provide accurate identification of 209 individual leopard frogs from a total set of 1386 images.

Optical security system for the protection of personal identification information.

PubMed

Doh, Yang-Hoi; Yoon, Jong-Soo; Choi, Kyung-Hyun; Alam, Mohammad S

2005-02-10

A new optical security system for the protection of personal identification information is proposed. First, authentication of the encrypted personal information is carried out by primary recognition of a personal identification number (PIN) with the proposed multiplexed minimum average correlation energy phase-encrypted (MMACE_p) filter. The MMACE_p filter, synthesized with phase-encrypted training images, can increase the discrimination capability and prevent the leak of personal identification information. After the PIN is recognized, speedy authentication of personal information can be achieved through one-to-one optical correlation by means of the optical wavelet filter. The possibility of information counterfeiting can be significantly decreased with the double-identification process. Simulation results demonstrate the effectiveness of the proposed technique.

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

NASA Astrophysics Data System (ADS)

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.

Comparison of Landsat Thematic Mapper and Geophysical and Environmental Research Imaging Spectrometer data for the Cuprite mining district, Esmeralda, and Nye counties, Nevada

NASA Technical Reports Server (NTRS)

Kierein-Young, Kathryn S.; Kruse, Fred A.

1989-01-01

Landsat TM images and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data were analyzed for the Cuprite mining district and compared to available geologic and alteration maps of the area. The TM data, with 30 m resolution and 6 broadbands, allowed discrimination of general mineral groups. Clay minerals, playa deposits, and unaltered rocks were mapped as discrete spectral units using the TM data, but specific minerals were not determined, and definition of the individual alteration zones was not possible. The GERIS, with 15 m spatial resolution and 63 spectral bands, permitted construction of complete spectra and identification of specific minerals. Detailed spectra extracted from the images provided the ability to identify the minerals alunite, kaolinite, hematite, and buddingtonite by their spectral characteristics. The GERIS data show a roughly concentrically zoned hydrothermal system. The mineralogy mapped with the aircraft system conforms to previous field and multispectral image mapping. However, identification of individual minerals and spatial display of the dominant mineralogy add information that can be used to help determine the morphology and genetic origin of the hydrothermal system.

A numerical study of sensory-guided multiple views for improved object identification

NASA Astrophysics Data System (ADS)

Blakeslee, B. A.; Zelnio, E. G.; Koditschek, D. E.

2014-06-01

We explore the potential on-line adjustment of sensory controls for improved object identification and discrimination in the context of a simulated high resolution camera system carried onboard a maneuverable robotic platform that can actively choose its observational position and pose. Our early numerical studies suggest the significant efficacy and enhanced performance achieved by even very simple feedback-driven iteration of the view in contrast to identification from a fixed pose, uninformed by any active adaptation. Specifically, we contrast the discriminative performance of the same conventional classification system when informed by: a random glance at a vehicle; two random glances at a vehicle; or a random glance followed by a guided second look. After each glance, edge detection algorithms isolate the most salient features of the image and template matching is performed through the use of the Hausdor↵ distance, comparing the simulated sensed images with reference images of the vehicles. We present initial simulation statistics that overwhelmingly favor the third scenario. We conclude with a sketch of our near-future steps in this study that will entail: the incorporation of more sophisticated image processing and template matching algorithms; more complex discrimination tasks such as distinguishing between two similar vehicles or vehicles in motion; more realistic models of the observers mobility including platform dynamics and eventually environmental constraints; and expanding the sensing task beyond the identification of a specified object selected from a pre-defined library of alternatives.

Preparing a collection of radiology examinations for distribution and retrieval.

PubMed

Demner-Fushman, Dina; Kohli, Marc D; Rosenman, Marc B; Shooshan, Sonya E; Rodriguez, Laritza; Antani, Sameer; Thoma, George R; McDonald, Clement J

2016-03-01

Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/). Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government employees and is in the public domain in the US.

Particle identification at an asymmetric B Factory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coyle, P.; Eigen, G.; Hitlin, D.

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{sup 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 distributionmore » 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 D conclude the chapter. 56 refs., 64 figs., 13 tabs.« less

A computational approach to real-time image processing for serial time-encoded amplified microscopy

NASA Astrophysics Data System (ADS)

Oikawa, Minoru; Hiyama, Daisuke; Hirayama, Ryuji; Hasegawa, Satoki; Endo, Yutaka; Sugie, Takahisa; Tsumura, Norimichi; Kuroshima, Mai; Maki, Masanori; Okada, Genki; Lei, Cheng; Ozeki, Yasuyuki; Goda, Keisuke; Shimobaba, Tomoyoshi

2016-03-01

High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.

Semi-Automated Identification of Rocks in Images

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin; Castano, Andres; Anderson, Robert

2006-01-01

Rock Identification Toolkit Suite is a computer program that assists users in identifying and characterizing rocks shown in images returned by the Mars Explorer Rover mission. Included in the program are components for automated finding of rocks, interactive adjustments of outlines of rocks, active contouring of rocks, and automated analysis of shapes in two dimensions. The program assists users in evaluating the surface properties of rocks and soil and reports basic properties of rocks. The program requires either the Mac OS X operating system running on a G4 (or more capable) processor or a Linux operating system running on a Pentium (or more capable) processor, plus at least 128MB of random-access memory.

Biometric recognition using 3D ear shape.

PubMed

Yan, Ping; Bowyer, Kevin W

2007-08-01

Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.

Infrared hyperspectral imaging sensor for gas detection

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele

2000-11-01

A small light weight man portable imaging spectrometer has many applications; gas leak detection, flare analysis, threat warning, chemical agent detection, just to name a few. With support from the US Air Force and Navy, Pacific Advanced Technology has developed a small man portable hyperspectral imaging sensor with an embedded DSP processor for real time processing that is capable of remotely imaging various targets such as gas plums, flames and camouflaged targets. Based upon their spectral signature the species and concentration of gases can be determined. This system has been field tested at numerous places including White Mountain, CA, Edwards AFB, and Vandenberg AFB. Recently evaluation of the system for gas detection has been performed. This paper presents these results. The system uses a conventional infrared camera fitted with a diffractive optic that images as well as disperses the incident radiation to form spectral images that are collected in band sequential mode. Because the diffractive optic performs both imaging and spectral filtering, the lens system consists of only a single element that is small, light weight and robust, thus allowing man portability. The number of spectral bands are programmable such that only those bands of interest need to be collected. The system is entirely passive, therefore, easily used in a covert operation. Currently Pacific Advanced Technology is working on the next generation of this camera system that will have both an embedded processor as well as an embedded digital signal processor in a small hand held camera configuration. This will allow the implementation of signal and image processing algorithms for gas detection and identification in real time. This paper presents field test data on gas detection and identification as well as discuss the signal and image processing used to enhance the gas visibility. Flow rates as low as 0.01 cubic feet per minute have been imaged with this system.

A Novel Imaging System Distinguishes Neoplastic from Normal Tissue During Resection of Soft Tissue Sarcomas and Mast Cell Tumors in Dogs.

PubMed

Bartholf DeWitt, Suzanne; Eward, William C; Eward, Cindy A; Lazarides, Alexander L; Whitley, Melodi Javid; Ferrer, Jorge M; Brigman, Brian E; Kirsch, David G; Berg, John

2016-08-01

To assess the ability of a novel imaging system designed for intraoperative detection of residual cancer in tumor beds to distinguish neoplastic from normal tissue in dogs undergoing resection of soft tissue sarcoma (STS) and mast cell tumor (MCT). Non-randomized prospective clinical trial. 12 dogs with STS and 7 dogs with MCT. A fluorescent imaging agent that is activated by proteases in vivo was administered to the dogs 4-6 or 24-26 hours before tumor resection. During surgery, a handheld imaging device was used to measure fluorescence intensity within the cancerous portion of the resected specimen and determine an intensity threshold for subsequent identification of cancer. Selected areas within the resected specimen and tumor bed were then imaged, and biopsies (n=101) were obtained from areas that did or did not have a fluorescence intensity exceeding the threshold. Results of intraoperative fluorescence and histology were compared. The imaging system correctly distinguished cancer from normal tissue in 93/101 biopsies (92%). Using histology as the reference, the sensitivity and specificity of the imaging system for identification of cancer in biopsies were 92% and 92%, respectively. There were 10/19 (53%) dogs which exhibited transient facial erythema soon after injection of the imaging agent which responded to but was not consistently prevented by intravenous diphenhydramine. A fluorescence-based imaging system designed for intraoperative use can distinguish canine soft tissue sarcoma (STS) and mast cell tumor (MCT) tissue from normal tissue with a high degree of accuracy. The system has potential to assist surgeons in assessing the adequacy of tumor resections during surgery, potentially reducing the risk of local tumor recurrence. Although responsive to antihistamines, the risk of hypersensitivity needs to be considered in light of the potential benefits of this imaging system in dogs. © Copyright 2016 by The American College of Veterinary Surgeons.

Sign Language Recognition System using Neural Network for Digital Hardware Implementation

NASA Astrophysics Data System (ADS)

Vargas, Lorena P.; Barba, Leiner; Torres, C. O.; Mattos, L.

2011-01-01

This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

Reducing Error Rates for Iris Image using higher Contrast in Normalization process

NASA Astrophysics Data System (ADS)

Aminu Ghali, Abdulrahman; Jamel, Sapiee; Abubakar Pindar, Zahraddeen; Hasssan Disina, Abdulkadir; Mat Daris, Mustafa

2017-08-01

Iris recognition system is the most secured, and faster means of identification and authentication. However, iris recognition system suffers a setback from blurring, low contrast and illumination due to low quality image which compromises the accuracy of the system. The acceptance or rejection rates of verified user depend solely on the quality of the image. In many cases, iris recognition system with low image contrast could falsely accept or reject user. Therefore this paper adopts Histogram Equalization Technique to address the problem of False Rejection Rate (FRR) and False Acceptance Rate (FAR) by enhancing the contrast of the iris image. A histogram equalization technique enhances the image quality and neutralizes the low contrast of the image at normalization stage. The experimental result shows that Histogram Equalization Technique has reduced FRR and FAR compared to the existing techniques.

Automatic retinal interest evaluation system (ARIES).

PubMed

Yin, Fengshou; Wong, Damon Wing Kee; Yow, Ai Ping; Lee, Beng Hai; Quan, Ying; Zhang, Zhuo; Gopalakrishnan, Kavitha; Li, Ruoying; Liu, Jiang

2014-01-01

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases such as glaucoma, age-related macular degeneration and diabetic retinopathy. However, in practice, retinal image quality is a big concern as automatic systems without consideration of degraded image quality will likely generate unreliable results. In this paper, an automatic retinal image quality assessment system (ARIES) is introduced to assess both image quality of the whole image and focal regions of interest. ARIES achieves 99.54% accuracy in distinguishing fundus images from other types of images through a retinal image identification step in a dataset of 35342 images. The system employs high level image quality measures (HIQM) to perform image quality assessment, and achieves areas under curve (AUCs) of 0.958 and 0.987 for whole image and optic disk region respectively in a testing dataset of 370 images. ARIES acts as a form of automatic quality control which ensures good quality images are used for processing, and can also be used to alert operators of poor quality images at the time of acquisition.

Evaluation of fingerprint deformation using optical coherence tomography

NASA Astrophysics Data System (ADS)

Gutierrez da Costa, Henrique S.; Maxey, Jessica R.; Silva, Luciano; Ellerbee, Audrey K.

2014-02-01

Biometric identification systems have important applications to privacy and security. The most widely used of these, print identification, is based on imaging patterns present in the fingers, hands and feet that are formed by the ridges, valleys and pores of the skin. Most modern print sensors acquire images of the finger when pressed against a sensor surface. Unfortunately, this pressure may result in deformations, characterized by changes in the sizes and relative distances of the print patterns, and such changes have been shown to negatively affect the performance of fingerprint identification algorithms. Optical coherence tomography (OCT) is a novel imaging technique that is capable of imaging the subsurface of biological tissue. Hence, OCT may be used to obtain images of subdermal skin structures from which one can extract an internal fingerprint. The internal fingerprint is very similar in structure to the commonly used external fingerprint and is of increasing interest in investigations of identify fraud. We proposed and tested metrics based on measurements calculated from external and internal fingerprints to evaluate the amount of deformation of the skin. Such metrics were used to test hypotheses about the differences of deformation between the internal and external images, variations with the type of finger and location inside the fingerprint.

The commercial use of satellite data to monitor the potato crop in the Columbia Basin

NASA Technical Reports Server (NTRS)

Waddington, George R., Jr.; Lamb, Frank G.

1990-01-01

The imaging of potato crops with satellites is described and evaluated in terms of the commercial application of the remotely sensed data. The identification and analysis of the crops is accomplished with multiple images acquired from the Landsat MSS and TM systems. The data are processed on a PC with image-procesing software which produces images of the seven 1024 x 1024 pixel windows which are subdivided into 21 512 x 512 pixel windows. Maximization of imaged data throughout the year aids in the identification of crop types by IR reflectance. The classification techniques involve the use of six or seven spectral classes for particular image dates. Comparisons with ground-truth data show good agreement; for example, potato fields are identified correctly 90 percent of the time. Acreage estimates and crop-condition assessments can be made from satellite data and used for corrective agricultural action.

Biometric template revocation

NASA Astrophysics Data System (ADS)

Arndt, Craig M.

2004-08-01

Biometric are a powerful technology for identifying humans both locally and at a distance. In order to perform identification or verification biometric systems capture an image of some biometric of a user or subject. The image is then converted mathematical to representation of the person call a template. Since we know that every human in the world is different each human will have different biometric images (different fingerprints, or faces, etc.). This is what makes biometrics useful for identification. However unlike a credit card number or a password to can be given to a person and later revoked if it is compromised and biometric is with the person for life. The problem then is to develop biometric templates witch can be easily revoked and reissued which are also unique to the user and can be easily used for identification and verification. In this paper we develop and present a method to generate a set of templates which are fully unique to the individual and also revocable. By using bases set compression algorithms in an n-dimensional orthogonal space we can represent a give biometric image in an infinite number of equally valued and unique ways. The verification and biometric matching system would be presented with a given template and revocation code. The code will then representing where in the sequence of n-dimensional vectors to start the recognition.

A bidirectional ACR-NEMA interface between the VA's DHCP Integrated Imaging System and the Siemens-Loral PACS.

PubMed Central

Kuzmak, P. M.; Dayhoff, R. E.

1992-01-01

There is a wide range of requirements for digital hospital imaging systems. Radiology needs very high resolution black and white images. Other diagnostic disciplines need high resolution color imaging capabilities. Images need to be displayed in many locations throughout the hospital. Different imaging systems within a hospital need to cooperate in order to show the whole picture. At the Baltimore VA Medical Center, the DHCP Integrated Imaging System and a commercial Picture Archiving and Communication System (PACS) work in concert to provide a wide-range of departmental and hospital-wide imaging capabilities. An interface between the DHCP and the Siemens-Loral PACS systems enables patient text and image data to be passed between the two systems. The interface uses ACR-NEMA 2.0 Standard messages extended with shadow groups based on draft ACR-NEMA 3.0 prototypes. A Novell file server, accessible to both systems via Ethernet, is used to communicate all the messages. Patient identification information, orders, ADT, procedure status, changes, patient reports, and images are sent between the two systems across the interface. The systems together provide an extensive set of imaging capabilities for both the specialist and the general practitioner. PMID:1482906

A bidirectional ACR-NEMA interface between the VA's DHCP Integrated Imaging System and the Siemens-Loral PACS.

PubMed

Kuzmak, P M; Dayhoff, R E

1992-01-01

There is a wide range of requirements for digital hospital imaging systems. Radiology needs very high resolution black and white images. Other diagnostic disciplines need high resolution color imaging capabilities. Images need to be displayed in many locations throughout the hospital. Different imaging systems within a hospital need to cooperate in order to show the whole picture. At the Baltimore VA Medical Center, the DHCP Integrated Imaging System and a commercial Picture Archiving and Communication System (PACS) work in concert to provide a wide-range of departmental and hospital-wide imaging capabilities. An interface between the DHCP and the Siemens-Loral PACS systems enables patient text and image data to be passed between the two systems. The interface uses ACR-NEMA 2.0 Standard messages extended with shadow groups based on draft ACR-NEMA 3.0 prototypes. A Novell file server, accessible to both systems via Ethernet, is used to communicate all the messages. Patient identification information, orders, ADT, procedure status, changes, patient reports, and images are sent between the two systems across the interface. The systems together provide an extensive set of imaging capabilities for both the specialist and the general practitioner.

Forecasting the ocean optical environment in support of Navy mine warfare operations

NASA Astrophysics Data System (ADS)

Ladner, S. D.; Arnone, R.; Jolliff, J.; Casey, B.; Matulewski, K.

2012-06-01

A 3D ocean optical forecast system called TODS (Tactical Ocean Data System) has been developed to determine the performance of underwater LIDAR detection/identification systems. TODS fuses optical measurements from gliders, surface satellite optical properties, and 3D ocean forecast circulation models to extend the 2-dimensional surface satellite optics into a 3-dimensional optical volume including subsurface optical layers of beam attenuation coefficient (c) and diver visibility. Optical 3D nowcast and forecasts are combined with electro-optical identification (EOID) models to determine the underwater LIDAR imaging performance field used to identify subsurface mine threats in rapidly changing coastal regions. TODS was validated during a recent mine warfare exercise with Helicopter Mine Countermeasures Squadron (HM-14). Results include the uncertainties in the optical forecast and lidar performance and sensor tow height predictions that are based on visual detection and identification metrics using actual mine target images from the EOID system. TODS is a new capability of coupling the 3D optical environment and EOID system performance and is proving important for the MIW community as both a tactical decision aid and for use in operational planning, improving timeliness and efficiency in clearance operations.

49 CFR 579.4 - Terminology.

Code of Federal Regulations, 2014 CFR

2014-10-01

... defined in S4 of § 571.213 of this chapter. The term Tire Identification Number (TIN) is the “tire..., fasteners, etc.). Backover prevention system means a system that has a visual image of the area directly...

Recognition of blurred images by the method of moments.

PubMed

Flusser, J; Suk, T; Saic, S

1996-01-01

The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.

Mugshot Identification Database (MID)

National Institute of Standards and Technology Data Gateway

NIST Mugshot Identification Database (MID) (Web, free access)   NIST Special Database 18 is being distributed for use in development and testing of automated mugshot identification systems. The database consists of three CD-ROMs, containing a total of 3248 images of variable size using lossless compression. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

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

PubMed

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.

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

USGS Publications Warehouse

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 millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Classification of gram-positive and gram-negative foodborne pathogenic bacteria with hyperspectral microscope imaging

USDA-ARS?s Scientific Manuscript database

Optical method with hyperspectral microscope imaging (HMI) has potential for identification of foodborne pathogenic bacteria from microcolonies rapidly with a cell level. A HMI system that provides both spatial and spectral information could be an effective tool for analyzing spectral characteristic...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2012 CFR

2012-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR § 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2013 CFR

2013-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2014 CFR

2014-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2010 CFR

2010-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2011 CFR

2011-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

A network identity authentication system based on Fingerprint identification technology

NASA Astrophysics Data System (ADS)

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.

Cluster Method Analysis of K. S. C. Image

NASA Technical Reports Server (NTRS)

Rodriguez, Joe, Jr.; Desai, M.

1997-01-01

Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

Multispectral imaging for biometrics

NASA Astrophysics Data System (ADS)

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsunobu, Y; Shiotsuki, K; Morishita, J

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 imagemore » 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.« less

An automated distinction of DICOM images for lung cancer CAD system

NASA Astrophysics Data System (ADS)

Suzuki, H.; Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nishitani, H.; Ohmatsu, H.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2009-02-01

Automated distinction of medical images is an important preprocessing in Computer-Aided Diagnosis (CAD) systems. The CAD systems have been developed using medical image sets with specific scan conditions and body parts. However, varied examinations are performed in medical sites. The specification of the examination is contained into DICOM textual meta information. Most DICOM textual meta information can be considered reliable, however the body part information cannot always be considered reliable. In this paper, we describe an automated distinction of DICOM images as a preprocessing for lung cancer CAD system. Our approach uses DICOM textual meta information and low cost image processing. Firstly, the textual meta information such as scan conditions of DICOM image is distinguished. Secondly, the DICOM image is set to distinguish the body parts which are identified by image processing. The identification of body parts is based on anatomical structure which is represented by features of three regions, body tissue, bone, and air. The method is effective to the practical use of lung cancer CAD system in medical sites.

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

PubMed Central

Kuzy, Jesse; Li, Changying

2017-01-01

Detection of foreign matter in cleaned cotton is instrumental to accurately grading cotton quality, which in turn impacts the marketability of the cotton. Current grading systems return estimates of the amount of foreign matter present, but provide no information about the identity of the contaminants. This paper explores the use of pulsed thermographic analysis to detect and identify cotton foreign matter. The design and implementation of a pulsed thermographic analysis system is described. A sample set of 240 foreign matter and cotton lint samples were collected. Hand-crafted waveform features and frequency-domain features were extracted and analyzed for statistical significance. Classification was performed on these features using linear discriminant analysis and support vector machines. Using waveform features and support vector machine classifiers, detection of cotton foreign matter was performed with 99.17% accuracy. Using frequency-domain features and linear discriminant analysis, identification was performed with 90.00% accuracy. These results demonstrate that pulsed thermographic imaging analysis produces data which is of significant utility for the detection and identification of cotton foreign matter. PMID:28273848

The Fundamentals of Thermal Imaging Systems.

DTIC Science & Technology

1979-05-10

detection , recognition, or identification, of real ’coene objects aire discussed. It is hoped that the text will be useful to FLIR designers, evaluators...AND ANDERSON EXPERIMENT ........................ 205 Appendix F - BASIC SNR AND DETECTIVITY RELATIONS ................................... 209 Appendix... detection , recognition, or identification, of real scene objects are discussed. I• It is hoped that the material in the text will be useful to

Autonomous identification of matrices in the APNea system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hensley, D.

1995-12-31

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 sufficientmore » 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.« less

Autonomous identification of matrices in the APNea System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hensley, D.

1995-12-31

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 sufficientmore » 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.« less

[Different wavelengths selection methods for identification of early blight on tomato leaves by using hyperspectral imaging technique].

PubMed

Cheng, Shu-Xi; Xie, Chuan-Qi; Wang, Qiao-Nan; He, Yong; Shao, Yong-Ni

2014-05-01

Identification of early blight on tomato leaves by using hyperspectral imaging technique based on different effective wavelengths selection methods (successive projections algorithm, SPA; x-loading weights, x-LW; gram-schmidt orthogonaliza-tion, GSO) was studied in the present paper. Hyperspectral images of seventy healthy and seventy infected tomato leaves were obtained by hyperspectral imaging system across the wavelength range of 380-1023 nm. Reflectance of all pixels in region of interest (ROI) was extracted by ENVI 4. 7 software. Least squares-support vector machine (LS-SVM) model was established based on the full spectral wavelengths. It obtained an excellent result with the highest identification accuracy (100%) in both calibration and prediction sets. Then, EW-LS-SVM and EW-LDA models were established based on the selected wavelengths suggested by SPA, x-LW and GSO, respectively. The results showed that all of the EW-LS-SVM and EW-LDA models performed well with the identification accuracy of 100% in EW-LS-SVM model and 100%, 100% and 97. 83% in EW-LDA model, respectively. Moreover, the number of input wavelengths of SPA-LS-SVM, x-LW-LS-SVM and GSO-LS-SVM models were four (492, 550, 633 and 680 nm), three (631, 719 and 747 nm) and two (533 and 657 nm), respectively. Fewer input variables were beneficial for the development of identification instrument. It demonstrated that it is feasible to identify early blight on tomato leaves by using hyperspectral imaging, and SPA, x-LW and GSO were effective wavelengths selection methods.

Qpais: A Web-Based Expert System for Assistedidentification of Quarantine Stored Insect Pests

NASA Astrophysics Data System (ADS)

Huang, Han; Rajotte, Edwin G.; Li, Zhihong; Chen, Ke; Zhang, Shengfang

Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.

21 CFR 884.6200 - Assisted reproduction laser system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Assisted reproduction laser system. 884.6200... Assisted reproduction laser system. (a) Identification. The assisted reproduction laser system is a device that images, targets, and controls the power and pulse duration of a laser beam used to ablate a small...

21 CFR 884.6200 - Assisted reproduction laser system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Assisted reproduction laser system. 884.6200... Assisted reproduction laser system. (a) Identification. The assisted reproduction laser system is a device that images, targets, and controls the power and pulse duration of a laser beam used to ablate a small...

21 CFR 884.6200 - Assisted reproduction laser system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Assisted reproduction laser system. 884.6200... Assisted reproduction laser system. (a) Identification. The assisted reproduction laser system is a device that images, targets, and controls the power and pulse duration of a laser beam used to ablate a small...

21 CFR 884.6200 - Assisted reproduction laser system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Assisted reproduction laser system. 884.6200... Assisted reproduction laser system. (a) Identification. The assisted reproduction laser system is a device that images, targets, and controls the power and pulse duration of a laser beam used to ablate a small...

21 CFR 884.6200 - Assisted reproduction laser system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Assisted reproduction laser system. 884.6200... Assisted reproduction laser system. (a) Identification. The assisted reproduction laser system is a device that images, targets, and controls the power and pulse duration of a laser beam used to ablate a small...

Imaging and identification of waterborne parasites using a chip-scale microscope.

PubMed

Lee, Seung Ah; Erath, Jessey; Zheng, Guoan; Ou, Xiaoze; Willems, Phil; Eichinger, Daniel; Rodriguez, Ana; Yang, Changhuei

2014-01-01

We demonstrate a compact portable imaging system for the detection of waterborne parasites in resource-limited settings. The previously demonstrated sub-pixel sweeping microscopy (SPSM) technique is a lens-less imaging scheme that can achieve high-resolution (<1 µm) bright-field imaging over a large field-of-view (5.7 mm×4.3 mm). A chip-scale microscope system, based on the SPSM technique, can be used for automated and high-throughput imaging of protozoan parasite cysts for the effective diagnosis of waterborne enteric parasite infection. We successfully imaged and identified three major types of enteric parasite cysts, Giardia, Cryptosporidium, and Entamoeba, which can be found in fecal samples from infected patients. We believe that this compact imaging system can serve well as a diagnostic device in challenging environments, such as rural settings or emergency outbreaks.

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

PubMed

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.

Developing the Interstate Identification Index/Federal Bureau of Investigation (III/FBI) system for providing timely criminal and civil identification and criminal history information to the nation's law enforcement agencies

NASA Astrophysics Data System (ADS)

Copeland, Patricia L.; Shugars, James

1997-02-01

The Federal Bureau of Investigation (FBI) is currently developing a new system to provide timely criminal and civil identities and criminal history information to the nation's local, state, and federal users. The Integrated Automated Fingerprint Identification System (IAFIS), an upgrade to the existing Identification Division Automated Services (IDAS) System, is scheduled for implementation in 1999 at the new FBI facility in Clarksburg, West Virginia. IAFIS will offer new capabilities for electronic transmittal of fingerprint cards to the FBI, an improved fingerprint matching algorithm, and electronic maintenance of fingerprints and photo images. The Interstate Identification Index (III/FBI) System is one of three segments comprising the umbrella IAFIS System. III/FBI provides repository, maintenance, and dissemination capabilities for the 40 million subject national criminal history database. III/FBI will perform over 1 million name searches each day. Demanding performance, reliability/maintainability/availability, and flexibility/expandability requirements make III/FBI an architectural challenge to the system developers. This paper will discuss these driving requirements and present the technical solutions in terms of leading edge hardware and software.

Design of biometrics identification system on palm vein using infrared light

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

People counting and re-identification using fusion of video camera and laser scanner

NASA Astrophysics Data System (ADS)

Ling, Bo; Olivera, Santiago; Wagley, Raj

2016-05-01

We present a system for people counting and re-identification. It can be used by transit and homeland security agencies. Under FTA SBIR program, we have developed a preliminary system for transit passenger counting and re-identification using a laser scanner and video camera. The laser scanner is used to identify the locations of passenger's head and shoulder in an image, a challenging task in crowed environment. It can also estimate the passenger height without prior calibration. Various color models have been applied to form color signatures. Finally, using a statistical fusion and classification scheme, passengers are counted and re-identified.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Holistic face processing can inhibit recognition of forensic facial composites.

PubMed

McIntyre, Alex H; Hancock, Peter J B; Frowd, Charlie D; Langton, Stephen R H

2016-04-01

Facial composite systems help eyewitnesses to show the appearance of criminals. However, likenesses created by unfamiliar witnesses will not be completely accurate, and people familiar with the target can find them difficult to identify. Faces are processed holistically; we explore whether this impairs identification of inaccurate composite images and whether recognition can be improved. In Experiment 1 (n = 64) an imaging technique was used to make composites of celebrity faces more accurate and identification was contrasted with the original composite images. Corrected composites were better recognized, confirming that errors in production of the likenesses impair identification. The influence of holistic face processing was explored by misaligning the top and bottom parts of the composites (cf. Young, Hellawell, & Hay, 1987). Misalignment impaired recognition of corrected composites but identification of the original, inaccurate composites significantly improved. This effect was replicated with facial composites of noncelebrities in Experiment 2 (n = 57). We conclude that, like real faces, facial composites are processed holistically: recognition is impaired because unlike real faces, composites contain inaccuracies and holistic face processing makes it difficult to perceive identifiable features. This effect was consistent across composites of celebrities and composites of people who are personally familiar. Our findings suggest that identification of forensic facial composites can be enhanced by presenting composites in a misaligned format. (c) 2016 APA, all rights reserved).

A theory of fine structure image models with an application to detection and classification of dementia.

PubMed

O'Neill, William; Penn, Richard; Werner, Michael; Thomas, Justin

2015-06-01

Estimation of stochastic process models from data is a common application of time series analysis methods. Such system identification processes are often cast as hypothesis testing exercises whose intent is to estimate model parameters and test them for statistical significance. Ordinary least squares (OLS) regression and the Levenberg-Marquardt algorithm (LMA) have proven invaluable computational tools for models being described by non-homogeneous, linear, stationary, ordinary differential equations. In this paper we extend stochastic model identification to linear, stationary, partial differential equations in two independent variables (2D) and show that OLS and LMA apply equally well to these systems. The method employs an original nonparametric statistic as a test for the significance of estimated parameters. We show gray scale and color images are special cases of 2D systems satisfying a particular autoregressive partial difference equation which estimates an analogous partial differential equation. Several applications to medical image modeling and classification illustrate the method by correctly classifying demented and normal OLS models of axial magnetic resonance brain scans according to subject Mini Mental State Exam (MMSE) scores. Comparison with 13 image classifiers from the literature indicates our classifier is at least 14 times faster than any of them and has a classification accuracy better than all but one. Our modeling method applies to any linear, stationary, partial differential equation and the method is readily extended to 3D whole-organ systems. Further, in addition to being a robust image classifier, estimated image models offer insights into which parameters carry the most diagnostic image information and thereby suggest finer divisions could be made within a class. Image models can be estimated in milliseconds which translate to whole-organ models in seconds; such runtimes could make real-time medicine and surgery modeling possible.

R&D on a Detector for Very High Momentum Charged Hadron Identification in ALICE

NASA Astrophysics Data System (ADS)

Gallas, A.

2006-04-01

The latest theoretical and experimental results from experiments at RHIC suggest investigating a physics domain in heavy ion collisions for pt higher than the one planned to be covered at present by the Particle Identification (PID) system of the ALICE experiment. We present here a possible upgrade of the High Momentum Particle Identification Detector (HMPID) based on the idea of the Threshold Imaging Cherenkov (TIC) detector operated for the first time by the NA44 experiment.

Optical correlators for recognition of human face thermal images

NASA Astrophysics Data System (ADS)

Bauer, Joanna; Podbielska, Halina; Suchwalko, Artur; Mazurkiewicz, Jacek

2005-09-01

In this paper, the application of the optical correlators for face thermograms recognition is described. The thermograms were colleted from 27 individuals. For each person 10 pictures in different conditions were recorded and the data base composed of 270 images was prepared. Two biometric systems based on joint transform correlator and 4f correlator were built. Each system was designed for realizing two various tasks: verification and identification. The recognition systems were tested and evaluated according to the Face Recognition Vendor Tests (FRVT).

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

NASA Astrophysics Data System (ADS)

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.

Calibration of a system to collect visible-light polarization data for classification of geosynchronous satellites

NASA Astrophysics Data System (ADS)

Speicher, Andy; Matin, Mohammad; Tippets, Roger; Chun, Francis

2014-09-01

In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. The objective of this study was to calibrate a system to exploit the optical signature of unresolved geosynchronous satellite images by collecting polarization data in the visible wavelengths for the purpose of revealing discriminating features. These features may lead to positive identification or classification of each satellite. The system was calibrated with an algorithm and process that takes raw observation data from a two-channel polarimeter and converts it to Stokes parameters S0 and S1. This instrumentation is a new asset for the United States Air Force Academy (USAFA) Department of Physics and consists of one 20-inch Ritchey-Chretien telescope and a dual focal plane system fed with a polarizing beam splitter. This study calibrated the system and collected preliminary polarization data on five geosynchronous satellites to validate performance. Preliminary data revealed that each of the five satellites had a different polarization signature that could potentially lead to identification in future studies.

Noninvasive forward-scattering system for rapid detection, characterization, and identification of Listeria colonies: image processing and data analysis

NASA Astrophysics Data System (ADS)

Rajwa, Bartek; Bayraktar, Bulent; Banada, Padmapriya P.; Huff, Karleigh; Bae, Euiwon; Hirleman, E. Daniel; Bhunia, Arun K.; Robinson, J. Paul

2006-10-01

Bacterial contamination by Listeria monocytogenes puts the public at risk and is also costly for the food-processing industry. Traditional methods for pathogen identification require complicated sample preparation for reliable results. Previously, we have reported development of a noninvasive optical forward-scattering system for rapid identification of Listeria colonies grown on solid surfaces. The presented system included application of computer-vision and patternrecognition techniques to classify scatter pattern formed by bacterial colonies irradiated with laser light. This report shows an extension of the proposed method. A new scatterometer equipped with a high-resolution CCD chip and application of two additional sets of image features for classification allow for higher accuracy and lower error rates. Features based on Zernike moments are supplemented by Tchebichef moments, and Haralick texture descriptors in the new version of the algorithm. Fisher's criterion has been used for feature selection to decrease the training time of machine learning systems. An algorithm based on support vector machines was used for classification of patterns. Low error rates determined by cross-validation, reproducibility of the measurements, and robustness of the system prove that the proposed technology can be implemented in automated devices for detection and classification of pathogenic bacteria.

Extending the imaging volume for biometric iris recognition.

PubMed

Narayanswamy, Ramkumar; Johnson, Gregory E; Silveira, Paulo E X; Wach, Hans B

2005-02-10

The use of the human iris as a biometric has recently attracted significant interest in the area of security applications. The need to capture an iris without active user cooperation places demands on the optical system. Unlike a traditional optical design, in which a large imaging volume is traded off for diminished imaging resolution and capacity for collecting light, Wavefront Coded imaging is a computational imaging technology capable of expanding the imaging volume while maintaining an accurate and robust iris identification capability. We apply Wavefront Coded imaging to extend the imaging volume of the iris recognition application.

A novel thermal face recognition approach using face pattern words

NASA Astrophysics Data System (ADS)

Zheng, Yufeng

2010-04-01

A reliable thermal face recognition system can enhance the national security applications such as prevention against terrorism, surveillance, monitoring and tracking, especially at nighttime. The system can be applied at airports, customs or high-alert facilities (e.g., nuclear power plant) for 24 hours a day. In this paper, we propose a novel face recognition approach utilizing thermal (long wave infrared) face images that can automatically identify a subject at both daytime and nighttime. With a properly acquired thermal image (as a query image) in monitoring zone, the following processes will be employed: normalization and denoising, face detection, face alignment, face masking, Gabor wavelet transform, face pattern words (FPWs) creation, face identification by similarity measure (Hamming distance). If eyeglasses are present on a subject's face, an eyeglasses mask will be automatically extracted from the querying face image, and then masked with all comparing FPWs (no more transforms). A high identification rate (97.44% with Top-1 match) has been achieved upon our preliminary face dataset (of 39 subjects) from the proposed approach regardless operating time and glasses-wearing condition.e

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

Text block identification in restoration process of Javanese script damage

NASA Astrophysics Data System (ADS)

Himamunanto, A. R.; Setyowati, E.

2018-05-01

Generally, in a sheet of documents there are two objects of information, namely text and image. A text block area in the sheet of manuscript is a vital object because the restoration process would be done only in this object. Text block or text area identification becomes an important step before. This paper describes the steps leading to the restoration of Java script destruction. The process stages are: pre-processing, identification of text block, segmentation, damage identification, restoration. The test result based on the input manuscript “Hamong Tani” show that the system works with a success rate of 82.07%

Automated texture-based identification of ovarian cancer in confocal microendoscope images

NASA Astrophysics Data System (ADS)

Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.

2005-03-01

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

Colony fingerprint for discrimination of microbial species based on lensless imaging of microcolonies

PubMed Central

Maeda, Yoshiaki; Dobashi, Hironori; Sugiyama, Yui; Saeki, Tatsuya; Lim, Tae-kyu; Harada, Manabu; Matsunaga, Tadashi; Yoshino, Tomoko

2017-01-01

Detection and identification of microbial species are crucial in a wide range of industries, including production of beverages, foods, cosmetics, and pharmaceuticals. Traditionally, colony formation and its morphological analysis (e.g., size, shape, and color) with a naked eye have been employed for this purpose. However, such a conventional method is time consuming, labor intensive, and not very reproducible. To overcome these problems, we propose a novel method that detects microcolonies (diameter 10–500 μm) using a lensless imaging system. When comparing colony images of five microorganisms from different genera (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans), the images showed obvious different features. Being closely related species, St. aureus and St. epidermidis resembled each other, but the imaging analysis could extract substantial information (colony fingerprints) including the morphological and physiological features, and linear discriminant analysis of the colony fingerprints distinguished these two species with 100% of accuracy. Because this system may offer many advantages such as high-throughput testing, lower costs, more compact equipment, and ease of automation, it holds promise for microbial detection and identification in various academic and industrial areas. PMID:28369067

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Hybrid neuro-fuzzy approach for automatic vehicle license plate recognition

NASA Astrophysics Data System (ADS)

Lee, Hsi-Chieh; Jong, Chung-Shi

1998-03-01

Most currently available vehicle identification systems use techniques such as R.F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory system. It is considered expensive to install a transponder in each vehicle and the malfunction of the transponder will result in the failure of the vehicle identification system. In this study, novel hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for the SimNet neuro-fuzzy system. To test the performance of the proposed system, three hundred and eighty vehicle image samples are taken by a digital camera. The license plate recognition success rate of the prototype is approximately 91% while the character recognition success rate of the prototype is approximately 97%.

PROBING THE MSP PRENATAL STAGE: THE OPTICAL IDENTIFICATION OF THE X-RAY BURSTER EXO 1745-248 IN TERZAN 5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferraro, F. R.; Pallanca, C.; Lanzoni, B.

2015-07-01

We report on the optical identification of the neutron star burster EXO 1745-248 in Terzan 5. The identification was performed by exploiting Hubble Space Telescope/Advanced Camera for Surveys images acquired in Director's Discretionary Time shortly after (approximately one month) the Swift detection of the X-ray burst. The comparison between these images and previous archival data revealed the presence of a star that is currently brightened by ∼3 mag, consistent with expectations during an X-ray outburst. The centroid of this object well agrees with the position, in the archival images, of a star located in the turn-off/sub-giant-branch region of Terzan 5.more » This supports the scenario that the companion should have recently filled its Roche Lobe. Such a system represents the prenatal stage of a millisecond pulsar, an evolutionary phase during which heavy mass accretion on the compact object occurs, thus producing X-ray outbursts and re-accelerating the neutron star.« less

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

PubMed

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.

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

PubMed Central

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

2016-01-01

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

PubMed

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

2016-10-25

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Comparison of conventional ultrasonography and ultrasonography-computed tomography fusion imaging for target identification using digital/real hybrid phantoms: a preliminary study.

PubMed

Soyama, Takeshi; Sakuhara, Yusuke; Kudo, Kohsuke; Abo, Daisuke; Wang, Jeff; Ito, Yoichi M; Hasegawa, Yu; Shirato, Hiroki

2016-07-01

This preliminary study compared ultrasonography-computed tomography (US-CT) fusion imaging and conventional ultrasonography (US) for accuracy and time required for target identification using a combination of real phantoms and sets of digitally modified computed tomography (CT) images (digital/real hybrid phantoms). In this randomized prospective study, 27 spheres visible on B-mode US were placed at depths of 3.5, 8.5, and 13.5 cm (nine spheres each). All 27 spheres were digitally erased from the CT images, and a radiopaque sphere was digitally placed at each of the 27 locations to create 27 different sets of CT images. Twenty clinicians were instructed to identify the sphere target using US alone and fusion imaging. The accuracy of target identification of the two methods was compared using McNemar's test. The mean time required for target identification and error distances were compared using paired t tests. At all three depths, target identification was more accurate and the mean time required for target identification was significantly less with US-CT fusion imaging than with US alone, and the mean error distances were also shorter with US-CT fusion imaging. US-CT fusion imaging was superior to US alone in terms of accurate and rapid identification of target lesions.

Competitive code-based fast palmprint identification using a set of cover trees

NASA Astrophysics Data System (ADS)

Yue, Feng; Zuo, Wangmeng; Zhang, David; Wang, Kuanquan

2009-06-01

A palmprint identification system recognizes a query palmprint image by searching for its nearest neighbor from among all the templates in a database. When applied on a large-scale identification system, it is often necessary to speed up the nearest-neighbor searching process. We use competitive code, which has very fast feature extraction and matching speed, for palmprint identification. To speed up the identification process, we extend the cover tree method and propose to use a set of cover trees to facilitate the fast and accurate nearest-neighbor searching. We can use the cover tree method because, as we show, the angular distance used in competitive code can be decomposed into a set of metrics. Using the Hong Kong PolyU palmprint database (version 2) and a large-scale palmprint database, our experimental results show that the proposed method searches for nearest neighbors faster than brute force searching.

Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

NASA Astrophysics Data System (ADS)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2015-04-01

Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Tracking of Cells with a Compact Microscope Imaging System with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark (Inventor)

2007-01-01

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously

Tracking of cells with a compact microscope imaging system with intelligent controls

NASA Technical Reports Server (NTRS)

McDowell, Mark (Inventor)

2007-01-01

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to auto-focus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

Identification and Imaging of Special Nuclear Materials and Contraband using Active x-ray Interrogation

NASA Astrophysics Data System (ADS)

Van Liew, Seth; Bertozzi, William; D'Olympia, Nathan; Franklin, Wilbur A.; Korbly, Stephen E.; Ledoux, Robert J.; Wilson, Cody M.

A x-ray inspection system utilizing a continuous-wave 9 MeV rhodotron x-ray source for scanning cargo containers is presented. This system scans for contraband, anomalies, stowaway passengers, and nuclear threats for trucks and towed cargo containers. A transmission image is generated concurrently with a 3D image of the cargo, the latter presenting material information in the form of atomic number and density. Neutrons from photofission are also detected during each scan. In addition, nuclear resonance fluorescence detectors are capable of identifying specific isotopes. This system has recently been deployed at the Port of Boston.

Content-based image exploitation for situational awareness

NASA Astrophysics Data System (ADS)

Gains, David

2008-04-01

Image exploitation is of increasing importance to the enterprise of building situational awareness from multi-source data. It involves image acquisition, identification of objects of interest in imagery, storage, search and retrieval of imagery, and the distribution of imagery over possibly bandwidth limited networks. This paper describes an image exploitation application that uses image content alone to detect objects of interest, and that automatically establishes and preserves spatial and temporal relationships between images, cameras and objects. The application features an intuitive user interface that exposes all images and information generated by the system to an operator thus facilitating the formation of situational awareness.

Identification and Assessment of Cardiac Amyloidosis by Myocardial Strain Analysis of Cardiac Magnetic Resonance Imaging.

PubMed

Oda, Seitaro; Utsunomiya, Daisuke; Nakaura, Takeshi; Yuki, Hideaki; Kidoh, Masafumi; Morita, Kosuke; Takashio, Seiji; Yamamuro, Megumi; Izumiya, Yasuhiro; Hirakawa, Kyoko; Ishida, Toshifumi; Tsujita, Kenichi; Ueda, Mitsuharu; Yamashita, Taro; Ando, Yukio; Hata, Hiroyuki; Yamashita, Yasuyuki

2017-06-23

We explored the usefulness of myocardial strain analysis on cardiac magnetic resonance imaging (CMR) scans for the identification of cardiac amyloidosis.Methods and Results:The 61 patients with systemic amyloidosis underwent 3.0-T CMR, including CMR tagging and late-gadolinium enhanced (LGE) imaging. The circumferential strain (CS) of LGE-positive and LGE-negative patients was measured on midventricular short-axis images and compared. Logistic regression modeling of CMR parameters was performed to detect patients with LGE-positive cardiac amyloidosis. Of the 61 patients with systemic amyloidosis 48 were LGE-positive and 13 were LGE-negative. The peak CS was significantly lower in the LGE-positive than in the LGE-negative patients (-9.5±2.3 vs. -13.3±1.4%, P<0.01). The variability in the peak CS time was significantly greater in the LGE-positive than in the LGE-negative patients (46.1±24.5 vs. 21.2±20.1 ms, P<0.01). The peak CS significantly correlated with clinical biomarkers. The sensitivity, specificity, and accuracy of the diagnostic model using CS parameters for the identification of LGE-positive amyloidosis were 93.8%, 76.9%, and 90.2%, respectively. Myocardial strain analysis by CMR helped detect LGE-positive amyloidosis without the need for contrast medium. The peak CS and variability in the peak CS time may correlate with the severity of cardiac amyloid deposition and may be more sensitive than LGE imaging for the detection of early cardiac disease in patients with amyloidosis.

Knowledge-based machine vision systems for space station automation

NASA Technical Reports Server (NTRS)

Ranganath, Heggere S.; Chipman, Laure J.

1989-01-01

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

[Teleradiology using uncompressed DICOM format via exclusive fiber-optic system].

PubMed

Okuda, Shigeo; Kuribayashi, Sachio; Hibi, Norihumi; Matsuura, Agato; Tani, Rie; Saga, Yasushi

2005-01-01

We developed a system for teleradiology using exclusive fiber optics for transferring images formatted in uncompressed DICOM. This system was built up with commercially available machines and software provided from various companies. We are now operating the system with five remote hospitals and have had one year of experience. The current system took advantage of the security and transfer efficiency of exclusive fiber optics. Uncompressed DICOM images were useful for the identification of cases and user-friendly for viewing. The reading room is located in our university hospital, and the location is convenient for consultation and discussion of cases.

Identification of suitable fundus images using automated quality assessment methods.

PubMed

Şevik, Uğur; Köse, Cemal; Berber, Tolga; Erdöl, Hidayet

2014-04-01

Retinal image quality assessment (IQA) is a crucial process for automated retinal image analysis systems to obtain an accurate and successful diagnosis of retinal diseases. Consequently, the first step in a good retinal image analysis system is measuring the quality of the input image. We present an approach for finding medically suitable retinal images for retinal diagnosis. We used a three-class grading system that consists of good, bad, and outlier classes. We created a retinal image quality dataset with a total of 216 consecutive images called the Diabetic Retinopathy Image Database. We identified the suitable images within the good images for automatic retinal image analysis systems using a novel method. Subsequently, we evaluated our retinal image suitability approach using the Digital Retinal Images for Vessel Extraction and Standard Diabetic Retinopathy Database Calibration level 1 public datasets. The results were measured through the F1 metric, which is a harmonic mean of precision and recall metrics. The highest F1 scores of the IQA tests were 99.60%, 96.50%, and 85.00% for good, bad, and outlier classes, respectively. Additionally, the accuracy of our suitable image detection approach was 98.08%. Our approach can be integrated into any automatic retinal analysis system with sufficient performance scores.

A high-speed tracking algorithm for dense granular media

NASA Astrophysics Data System (ADS)

Cerda, Mauricio; Navarro, Cristóbal A.; Silva, Juan; Waitukaitis, Scott R.; Mujica, Nicolás; Hitschfeld, Nancy

2018-06-01

Many fields of study, including medical imaging, granular physics, colloidal physics, and active matter, require the precise identification and tracking of particle-like objects in images. While many algorithms exist to track particles in diffuse conditions, these often perform poorly when particles are densely packed together-as in, for example, solid-like systems of granular materials. Incorrect particle identification can have significant effects on the calculation of physical quantities, which makes the development of more precise and faster tracking algorithms a worthwhile endeavor. In this work, we present a new tracking algorithm to identify particles in dense systems that is both highly accurate and fast. We demonstrate the efficacy of our approach by analyzing images of dense, solid-state granular media, where we achieve an identification error of 5% in the worst evaluated cases. Going further, we propose a parallelization strategy for our algorithm using a GPU, which results in a speedup of up to 10 × when compared to a sequential CPU implementation in C and up to 40 × when compared to the reference MATLAB library widely used for particle tracking. Our results extend the capabilities of state-of-the-art particle tracking methods by allowing fast, high-fidelity detection in dense media at high resolutions.

Identification and classification of chemicals using terahertz reflective spectroscopic focal-plane imaging system.

PubMed

Zhong, Hua; Redo-Sanchez, Albert; Zhang, X-C

2006-10-02

We present terahertz (THz) reflective spectroscopic focal-plane imaging of four explosive and bio-chemical materials (2, 4-DNT, Theophylline, RDX and Glutamic Acid) at a standoff imaging distance of 0.4 m. The 2 dimension (2-D) nature of this technique enables a fast acquisition time and is very close to a camera-like operation, compared to the most commonly used point emission-detection and raster scanning configuration. The samples are identified by their absorption peaks extracted from the negative derivative of the reflection coefficient respect to the frequency (-dr/dv) of each pixel. Classification of the samples is achieved by using minimum distance classifier and neural network methods with a rate of accuracy above 80% and a false alarm rate below 8%. This result supports the future application of THz time-domain spectroscopy (TDS) in standoff distance sensing, imaging, and identification.

A Concealed Barcode Identification System Using Terahertz Time-domain Spectroscopy

NASA Astrophysics Data System (ADS)

Guan, Yu; Yamamoto, Manabu; Kitazawa, Toshiyuki; Tripathi, Saroj R.; Takeya, Kei; Kawase, Kodo

2015-03-01

We present a concealed terahertz barcode/chipless tag to achieve remote identification through an obstructing material using terahertz radiation. We show scanned terahertz reflection spectral images of barcodes concealed by a thick obstacle. A concealed and double- side printed terahertz barcode structure is proposed, and we demonstrate that our design has better performance in definition than a single-side printed barcode using terahertz time-domain spectroscopy. This technique combines the benefits of a chipless tag to read encoded information covered by an optically opaque material with low cost and a simple fabrication process. Simulations are also described, along with an explanation of the principle of the terahertz barcode identification system.

Rapid identification of Prototheca species by the API 20C system.

PubMed Central

Padhye, A A; Baker, J G; D'Amato, R F

1979-01-01

The conventional auxanographic method of testing for the assimilation of carbohydrates and alcohols by the various species of Prototheca requires at least 2 weeks of incubation at 25 to 30 degrees C before definitive results are obtained. Even though Prototheca spp., in culture as well as in fixed tissues, can be identified more rapidly by fluorescent-antibody techniques in which species-specific reagents are used, such diagnostic facilities and reagents are not available in most diagnostic laboratories. The API 20C clinical yeast identification system, a commercially available ready-to-use micromethod, was found to permit the definitive identification of P. stagnora, P. wickerhamii, and P. zopfii within 4 days. Images PMID:393722

Automated Root Tracking with "Root System Analyzer"

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Jin, Meina; Ockert, Charlotte; Bol, Roland; Leitner, Daniel

2015-04-01

Crucial factors for plant development are water and nutrient availability in soils. Thus, root architecture is a main aspect of plant productivity and needs to be accurately considered when describing root processes. Images of root architecture contain a huge amount of information, and image analysis helps to recover parameters describing certain root architectural and morphological traits. The majority of imaging systems for root systems are designed for two-dimensional images, such as RootReader2, GiA Roots, SmartRoot, EZ-Rhizo, and Growscreen, but most of them are semi-automated and involve mouse-clicks in each root by the user. "Root System Analyzer" is a new, fully automated approach for recovering root architectural parameters from two-dimensional images of root systems. Individual roots can still be corrected manually in a user interface if required. The algorithm starts with a sequence of segmented two-dimensional images showing the dynamic development of a root system. For each image, morphological operators are used for skeletonization. Based on this, a graph representation of the root system is created. A dynamic root architecture model helps to determine which edges of the graph belong to an individual root. The algorithm elongates each root at the root tip and simulates growth confined within the already existing graph representation. The increment of root elongation is calculated assuming constant growth. For each root, the algorithm finds all possible paths and elongates the root in the direction of the optimal path. In this way, each edge of the graph is assigned to one or more coherent roots. Image sequences of root systems are handled in such a way that the previous image is used as a starting point for the current image. The algorithm is implemented in a set of Matlab m-files. Output of Root System Analyzer is a data structure that includes for each root an identification number, the branching order, the time of emergence, the parent identification number, the distance between branching point to the parent root base, the root length, the root radius and the nodes that belong to each individual root path. This information is relevant for the analysis of dynamic root system development as well as the parameterisation of root architecture models. Here, we show results of Root System Analyzer applied to analyse the root systems of wheat plants grown in rhizotrons. Different treatments with respect to soil moisture and apatite concentrations were used to test the effects of those conditions on root system development. Photographs of the root systems were taken at high spatial and temporal resolution and root systems are automatically tracked.

Numerical correction of distorted images in full-field optical coherence tomography

NASA Astrophysics Data System (ADS)

Min, Gihyeon; Kim, Ju Wan; Choi, Woo June; Lee, Byeong Ha

2012-03-01

We propose a numerical method which can numerically correct the distorted en face images obtained with a full field optical coherence tomography (FF-OCT) system. It is shown that the FF-OCT image of the deep region of a biological sample is easily blurred or degraded because the sample has a refractive index (RI) much higher than its surrounding medium in general. It is analyzed that the focal plane of the imaging system is segregated from the imaging plane of the coherence-gated system due to the RI mismatch. This image-blurring phenomenon is experimentally confirmed by imaging the chrome pattern of a resolution test target through its glass substrate in water. Moreover, we demonstrate that the blurred image can be appreciably corrected by using the numerical correction process based on the Fresnel-Kirchhoff diffraction theory. The proposed correction method is applied to enhance the image of a human hair, which permits the distinct identification of the melanin granules inside the cortex layer of the hair shaft.

In vivo volumetric depth-resolved vasculature imaging of human limbus and sclera with 1 μm swept source phase-variance optical coherence angiography

NASA Astrophysics Data System (ADS)

Poddar, Raju; Zawadzki, Robert J.; Cortés, Dennis E.; Mannis, Mark J.; Werner, John S.

2015-06-01

We present in vivo volumetric depth-resolved vasculature images of the anterior segment of the human eye acquired with phase-variance based motion contrast using a high-speed (100 kHz, 105 A-scans/s) swept source optical coherence tomography system (SSOCT). High phase stability SSOCT imaging was achieved by using a computationally efficient phase stabilization approach. The human corneo-scleral junction and sclera were imaged with swept source phase-variance optical coherence angiography and compared with slit lamp images from the same eyes of normal subjects. Different features of the rich vascular system in the conjunctiva and episclera were visualized and described. This system can be used as a potential tool for ophthalmological research to determine changes in the outflow system, which may be helpful for identification of abnormalities that lead to glaucoma.

Aircraft engine-mounted camera system for long wavelength infrared imaging of in-service thermal barrier coated turbine blades

NASA Astrophysics Data System (ADS)

Markham, James; Cosgrove, Joseph; Scire, James; Haldeman, Charles; Agoos, Ian

2014-12-01

This paper announces the implementation of a long wavelength infrared camera to obtain high-speed thermal images of an aircraft engine's in-service thermal barrier coated turbine blades. Long wavelength thermal images were captured of first-stage blades. The achieved temporal and spatial resolutions allowed for the identification of cooling-hole locations. The software and synchronization components of the system allowed for the selection of any blade on the turbine wheel, with tuning capability to image from leading edge to trailing edge. Its first application delivered calibrated thermal images as a function of turbine rotational speed at both steady state conditions and during engine transients. In advance of presenting these data for the purpose of understanding engine operation, this paper focuses on the components of the system, verification of high-speed synchronized operation, and the integration of the system with the commercial jet engine test bed.

Aircraft engine-mounted camera system for long wavelength infrared imaging of in-service thermal barrier coated turbine blades.

PubMed

Markham, James; Cosgrove, Joseph; Scire, James; Haldeman, Charles; Agoos, Ian

2014-12-01

This paper announces the implementation of a long wavelength infrared camera to obtain high-speed thermal images of an aircraft engine's in-service thermal barrier coated turbine blades. Long wavelength thermal images were captured of first-stage blades. The achieved temporal and spatial resolutions allowed for the identification of cooling-hole locations. The software and synchronization components of the system allowed for the selection of any blade on the turbine wheel, with tuning capability to image from leading edge to trailing edge. Its first application delivered calibrated thermal images as a function of turbine rotational speed at both steady state conditions and during engine transients. In advance of presenting these data for the purpose of understanding engine operation, this paper focuses on the components of the system, verification of high-speed synchronized operation, and the integration of the system with the commercial jet engine test bed.

Identification of geostationary satellites using polarization data from unresolved images

NASA Astrophysics Data System (ADS)

Speicher, Andy

In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chretien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight satellites were identical buses to determine if identical buses could be correctly differentiated. When Stokes parameters were plotted against time and solar phase angle, the data indicates that there were distinguishing features in S0 (total intensity) and S1 (linear polarization) that may lead to positive identification or classification of each satellite.

Top-down mass spectrometry imaging of intact proteins by laser ablation ESI FT-ICR MS.

PubMed

Kiss, András; Smith, Donald F; Reschke, Brent R; Powell, Matthew J; Heeren, Ron M A

2014-05-01

Laser ablation ESI (LAESI) is a recent development in MS imaging. It has been shown that lipids and small metabolites can be imaged in various samples such as plant material, tissue sections or bacterial colonies without any sample pretreatment. Further, LAESI has been shown to produce multiply charged protein ions from liquids or solid surfaces. This presents a means to address one of the biggest challenges in MS imaging; the identification of proteins directly from biological tissue surfaces. Such identification is hindered by the lack of multiply charged proteins in common MALDI ion sources and the difficulty of performing tandem MS on such large, singly charged ions. We present here top-down identification of intact proteins from tissue with a LAESI ion source combined with a hybrid ion-trap FT-ICR mass spectrometer. The performance of the system was first tested with a standard protein with electron capture dissociation and infrared multiphoton dissociation fragmentation to prove the viability of LAESI FT-ICR for top-down proteomics. Finally, the imaging of a tissue section was performed, where a number of intact proteins were measured and the hemoglobin α chain was identified directly from tissue using CID and infrared multiphoton dissociation fragmentation. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rule-driven defect detection in CT images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2000-01-01

This paper deals with automated detection and identification of internal defects in hardwood logs using computed tomography (CT) images. We have developed a system that employs artificial neural networks to perform tentative classification of logs on a pixel-by-pixel basis. This approach achieves a high level of classification accuracy for several hardwood species (...

Earth resources sensor data handling system: NASA JSC version

NASA Technical Reports Server (NTRS)

1974-01-01

The design of the NASA JSC data handling system is presented. Data acquisition parameters and computer display formats and the flow of image data through the system, with recommendations for improving system efficiency are discussed along with modifications to existing data handling procedures which will allow utilization of data duplication techniques and the accurate identification of imagery.

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

PubMed

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.

Demonstration of a single-wavelength spectral-imaging-based Thai jasmine rice identification

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2011-07-01

A single-wavelength spectral-imaging-based Thai jasmine rice breed identification is demonstrated. Our nondestructive identification approach relies on a combination of fluorescent imaging and simple image processing techniques. Especially, we apply simple image thresholding, blob filtering, and image subtracting processes to either a 545 or a 575nm image in order to identify our desired Thai jasmine rice breed from others. Other key advantages include no waste product and fast identification time. In our demonstration, UVC light is used as our exciting light, a liquid crystal tunable optical filter is used as our wavelength seclector, and a digital camera with 640activepixels×480activepixels is used to capture the desired spectral image. Eight Thai rice breeds having similar size and shape are tested. Our experimental proof of concept shows that by suitably applying image thresholding, blob filtering, and image subtracting processes to the selected fluorescent image, the Thai jasmine rice breed can be identified with measured false acceptance rates of <22.9% and <25.7% for spectral images at 545 and 575nm wavelengths, respectively. A measured fast identification time is 25ms, showing high potential for real-time applications.

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

Rapid and non-destructive identification of water-injected beef samples using multispectral imaging analysis.

PubMed

Liu, Jinxia; Cao, Yue; Wang, Qiu; Pan, Wenjuan; Ma, Fei; Liu, Changhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

2016-01-01

Water-injected beef has aroused public concern as a major food-safety issue in meat products. In the study, the potential of multispectral imaging analysis in the visible and near-infrared (405-970 nm) regions was evaluated for identifying water-injected beef. A multispectral vision system was used to acquire images of beef injected with up to 21% content of water, and partial least squares regression (PLSR) algorithm was employed to establish prediction model, leading to quantitative estimations of actual water increase with a correlation coefficient (r) of 0.923. Subsequently, an optimized model was achieved by integrating spectral data with feature information extracted from ordinary RGB data, yielding better predictions (r = 0.946). Moreover, the prediction equation was transferred to each pixel within the images for visualizing the distribution of actual water increase. These results demonstrate the capability of multispectral imaging technology as a rapid and non-destructive tool for the identification of water-injected beef. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

Identification of inferior pancreaticoduodenal artery during pancreaticoduodenectomy using augmented reality-based navigation system.

PubMed

Onda, Shinji; Okamoto, Tomoyoshi; Kanehira, Masaru; Suzuki, Fumitake; Ito, Ryusuke; Fujioka, Shuichi; Suzuki, Naoki; Hattori, Asaki; Yanaga, Katsuhiko

2014-04-01

In pancreaticoduodenectomy (PD), early ligation of the inferior pancreaticoduodenal artery (IPDA) before efferent veins has been advocated to decrease blood loss by congestion of the pancreatic head to be resected. In this study, we herein report the utility of early identification of the IPDA using an augmented reality (AR)-based navigation system (NS). Seven nonconsecutive patients underwent PD using AR-based NS. After paired-point matching registration, the reconstructed image obtained by preoperative computed tomography (CT) was fused with a real-time operative field image and displayed on 3D monitors. The vascular reconstructed images, including the superior mesenteric artery, jejunal artery, and IPDA were visualized to facilitate image-guided surgical procedures. We compared operating time and intraoperative blood loss of six patients who successfully underwent identification of IPDA using AR-based NS (group A) with nine patients who underwent early ligation of IPDA without using AR (group B) and 18 patients who underwent a conventional PD (group C). The IPDA or the jejunal artery was rapidly identified and ligated in six patients. The mean operating time and intraoperative blood loss in group A was 415 min and 901 ml, respectively. There was no significant difference in operating time and intraoperative blood loss among the groups. The AR-based NS provided precise anatomical information, which allowed the surgeons to rapidly identify and perform early ligation of IPDA in PD. © 2013 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Electronic readout system for the Belle II imaging Time-Of-Propagation detector

NASA Astrophysics Data System (ADS)

Kotchetkov, Dmitri

2017-07-01

The imaging Time-Of-Propagation (iTOP) detector, constructed for the Belle II experiment at the SuperKEKB e+e- collider, is an 8192-channel high precision Cherenkov particle identification detector with timing resolution below 50 ps. To acquire data from the iTOP, a novel front-end electronic readout system was designed, built, and integrated. Switched-capacitor array application-specific integrated circuits are used to sample analog signals. Triggering, digitization, readout, and data transfer are controlled by Xilinx Zynq-7000 system on a chip devices.

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

PubMed

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.

Handheld THz security imaging

NASA Astrophysics Data System (ADS)

Duling, Irl N.

2016-05-01

Terahertz energy, with its ability to penetrate clothing and non-conductive materials, has held much promise in the area of security scanning. Millimeter wave systems (300 GHz and below) have been widely deployed. These systems have used full two-dimensional surface imaging, and have resulted in privacy concerns. Pulsed terahertz imaging, can detect the presence of unwanted objects without the need for two-dimensional photographic imaging. With high-speed waveform acquisition it is possible to create handheld tools that can be used to locate anomalies under clothing or headgear looking exclusively at either single point waveforms or cross-sectional images which do not pose a privacy concern. Identification of the anomaly to classify it as a potential threat or a benign object is also possible.

ACTH (Adrenocorticotropic Hormone) Test

MedlinePlus

... Time and International Normalized Ratio (PT/INR) PSEN1 Quantitative Immunoglobulins Red Blood Cell (RBC) Antibody Identification Red ... Health Network KidsHealth.org: Endocrine System Cushing's Support & Research Foundation See More See Less Related Images View ...

A plasmid-based reporter system for live cell imaging of dengue virus infected cells.

PubMed

Medin, Carey L; Valois, Sierra; Patkar, Chinmay G; Rothman, Alan L

2015-01-01

Cell culture models are used widely to study the effects of dengue virus (DENV) on host cell function. Current methods of identification of cells infected with an unmodified DENV requires fixation and permeablization of cells to allow DENV-specific antibody staining. This method does not permit imaging of viable cells over time. In this report, a plasmid-based reporter was developed to allow non-destructive identification of DENV-infected cells. The plasmid-based reporter was demonstrated to be broadly applicable to the four DENV serotypes, including low-passaged strains, and was specifically cleaved by the viral protease with minimal interference on viral production. This study reveals the potential for this novel reporter system to advance the studies of virus-host interactions during DENV infection. Copyright © 2014 Elsevier B.V. All rights reserved.

Dental caries imaging using hyperspectral stimulated Raman scattering microscopy

NASA Astrophysics Data System (ADS)

Wang, Zi; Zheng, Wei; Jian, Lin; Huang, Zhiwei

2016-03-01

We report the development of a polarization-resolved hyperspectral stimulated Raman scattering (SRS) imaging technique based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of dental caries. In our imaging system, hyperspectral SRS images (512×512 pixels) in both fingerprint region (800-1800 cm-1) and high-wavenumber region (2800-3600 cm-1) are acquired in minutes by scanning the wavelength of OPO output, which is a thousand times faster than conventional confocal micro Raman imaging. SRS spectra variations from normal enamel to caries obtained from the hyperspectral SRS images show the loss of phosphate and carbonate in the carious region. While polarization-resolved SRS images at 959 cm-1 demonstrate that the caries has higher depolarization ratio. Our results demonstrate that the polarization resolved-hyperspectral SRS imaging technique developed allows for rapid identification of the biochemical and structural changes of dental caries.

The fast iris image clarity evaluation based on Tenengrad and ROI selection

NASA Astrophysics Data System (ADS)

Gao, Shuqin; Han, Min; Cheng, Xu

2018-04-01

In iris recognition system, the clarity of iris image is an important factor that influences recognition effect. In the process of recognition, the blurred image may possibly be rejected by the automatic iris recognition system, which will lead to the failure of identification. Therefore it is necessary to evaluate the iris image definition before recognition. Considered the existing evaluation methods on iris image definition, we proposed a fast algorithm to evaluate the definition of iris image in this paper. In our algorithm, firstly ROI (Region of Interest) is extracted based on the reference point which is determined by using the feature of the light spots within the pupil, then Tenengrad operator is used to evaluate the iris image's definition. Experiment results show that, the iris image definition algorithm proposed in this paper could accurately distinguish the iris images of different clarity, and the algorithm has the merit of low computational complexity and more effectiveness.

Active imaging system performance model for target acquisition

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Teaney, Brian; Nguyen, Quang; Jacobs, Eddie L.; Halford, Carl E.; Tofsted, David H.

2007-04-01

The U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors Directorate has developed a laser-range-gated imaging system performance model for the detection, recognition, and identification of vehicle targets. The model is based on the established US Army RDECOM CERDEC NVESD sensor performance models of the human system response through an imaging system. The Java-based model, called NVLRG, accounts for the effect of active illumination, atmospheric attenuation, and turbulence effects relevant to LRG imagers, such as speckle and scintillation, and for the critical sensor and display components. This model can be used to assess the performance of recently proposed active SWIR systems through various trade studies. This paper will describe the NVLRG model in detail, discuss the validation of recent model components, present initial trade study results, and outline plans to validate and calibrate the end-to-end model with field data through human perception testing.

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

PubMed

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.

Personal Identification Using Fingernail Image Based on Correlation of Density Block

NASA Astrophysics Data System (ADS)

Noda, Mayumi; Saitoh, Fumihiko

This paper proposes an authentication using fingernail images by using the block segmentation matching. A fingernail is assumed to be a new physical character that is used for biometrics authentication. The proposed system is more effective than fingerprint authentication where psychological resistance and conformability are required. Since the block segmentation matching is useful for occlusion of an object, it is assumed to be robust to a partial change of fingernail. It is expected to enhance the difference of fingernails between persons. The experimental images of various lengths of fingernail and painted manicure were used for evaluation of system performance. The experimental results show that the proposed system obtains the sufficient accuracy to certificate individuals.

Dependency of Optimal Parameters of the IRIS Template on Image Quality and Border Detection Error

NASA Astrophysics Data System (ADS)

Matveev, I. A.; Novik, V. P.

2017-05-01

Generation of a template containing spatial-frequency features of iris is an important stage of identification. The template is obtained by a wavelet transform in an image region specified by iris borders. One of the main characteristics of the identification system is the value of recognition error, equal error rate (EER) is used as criterion here. The optimal values (in sense of minimizing the EER) of wavelet transform parameters depend on many factors: image quality, sharpness, size of characteristic objects, etc. It is hard to isolate these factors and their influences. The work presents an attempt to study an influence of following factors to EER: iris segmentation precision, defocus level, noise level. Several public domain iris image databases were involved in experiments. The images were subjected to modelled distortions of said types. The dependencies of wavelet parameter and EER values from the distortion levels were build. It is observed that the increase of the segmentation error and image noise leads to the increase of the optimal wavelength of the wavelets, whereas the increase of defocus level leads to decreasing of this value.

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

NASA Astrophysics Data System (ADS)

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 localization capability. Utilizing imaging information will show signal-to-noise gains over spectroscopic algorithms alone.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Classification of Non-Time-Locked Rapid Serial Visual Presentation Events for Brain-Computer Interaction Using Deep Learning

DTIC Science & Technology

2014-07-08

internction ( BCI ) system allows h uman subjects to communicate with or control an extemal device with their brain signals [1], or to use those brain...signals to interact with computers, environments, or even other humans [2]. One application of BCI is to use brnin signals to distinguish target...images within a large collection of non-target images [2]. Such BCI -based systems can drastically increase the speed of target identification in

More About The Video Event Trigger

NASA Technical Reports Server (NTRS)

Williams, Glenn L.

1996-01-01

Report presents additional information about system described in "Video Event Trigger" (LEW-15076). Digital electronic system processes video-image data to generate trigger signal when image shows significant change, such as motion, or appearance, disappearance, change in color, brightness, or dilation of object. Potential uses include monitoring of hallways, parking lots, and other areas during hours when supposed unoccupied, looking for fires, tracking airplanes or other moving objects, identification of missing or defective parts on production lines, and video recording of automobile crash tests.

Computational cameras for moving iris recognition

NASA Astrophysics Data System (ADS)

McCloskey, Scott; Venkatesha, Sharath

2015-05-01

Iris-based biometric identification is increasingly used for facility access and other security applications. Like all methods that exploit visual information, however, iris systems are limited by the quality of captured images. Optical defocus due to a small depth of field (DOF) is one such challenge, as is the acquisition of sharply-focused iris images from subjects in motion. This manuscript describes the application of computational motion-deblurring cameras to the problem of moving iris capture, from the underlying theory to system considerations and performance data.

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

NASA Astrophysics Data System (ADS)

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.

Extracting paleo-climate signals from sediment laminae: A new, automated image processing method

NASA Astrophysics Data System (ADS)

Gan, S. Q.; Scholz, C. A.

2010-12-01

Lake sediment laminations commonly represent depositional seasonality in lacustrine environments. Their occurrence and quantitative attributes contain various signals of their depositional environment, limnological conditions and climate. However, the identification and measurement of laminae remains a mainly manual process that is not only tedious and labor intensive, but also subjective and error prone. We present a batch method to identify laminae and extract lamina properties automatically and accurately from sediment core images. Our algorithm is focused on image enhancement that improves the signal-to-noise ratio and maximizes and normalizes image contrast. The unique feature of these algorithms is that they are all direction-sensitive, i.e., the algorithms treat images in the horizontal direction and vertical direction differently and independently. The core process of lamina identification is to use a one-dimensional (1-D) lamina identification algorithm to produce a lamina map, and to use image blob analyses and lamina connectivity analyses to aggregate and smash two-dimensional (2-D) lamina data for the best representation of fine-scale stratigraphy in the sediment profile. The primary output datasets of the system are definitions of laminae and primary color values for each pixel and each lamina in the depth direction; other derived datasets can be retrieved at users’ discretion. Sediment core images from Lake Hitchcock , USA and Lake Bosumtwi, Ghana, were used for algorithm development and testing. As a demonstration of the utility of the software, we processed sediment core images from the top of 50 meters of drill core (representing the past ~100 ky) from Lake Bosumtwi, Ghana.

A visual identification key utilizing both gestalt and analytic approaches to identification of Carices present in North America (Plantae, Cyperaceae)

PubMed Central

2013-01-01

Abstract Images are a critical part of the identification process because they enable direct, immediate and relatively unmediated comparisons between a specimen being identified and one or more reference specimens. The Carices Interactive Visual Identification Key (CIVIK) is a novel tool for identification of North American Carex species, the largest vascular plant genus in North America, and two less numerous closely-related genera, Cymophyllus and Kobresia. CIVIK incorporates 1288 high-resolution tiled image sets that allow users to zoom in to view minute structures that are crucial at times for identification in these genera. Morphological data are derived from the earlier Carex Interactive Identification Key (CIIK) which in turn used data from the Flora of North America treatments. In this new iteration, images can be viewed in a grid or histogram format, allowing multiple representations of data. In both formats the images are fully zoomable. PMID:24723777

Crack identification for rigid pavements using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bahaddin Ersoz, Ahmet; Pekcan, Onur; Teke, Turker

2017-09-01

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Tools for quality control of fingerprint databases

NASA Astrophysics Data System (ADS)

Swann, B. Scott; Libert, John M.; Lepley, Margaret A.

2010-04-01

Integrity of fingerprint data is essential to biometric and forensic applications. Accordingly, the FBI's Criminal Justice Information Services (CJIS) Division has sponsored development of software tools to facilitate quality control functions relative to maintaining its fingerprint data assets inherent to the Integrated Automated Fingerprint Identification System (IAFIS) and Next Generation Identification (NGI). This paper provides an introduction of two such tools. The first FBI-sponsored tool was developed by the National Institute of Standards and Technology (NIST) and examines and detects the spectral signature of the ridge-flow structure characteristic of friction ridge skin. The Spectral Image Validation/Verification (SIVV) utility differentiates fingerprints from non-fingerprints, including blank frames or segmentation failures erroneously included in data; provides a "first look" at image quality; and can identify anomalies in sample rates of scanned images. The SIVV utility might detect errors in individual 10-print fingerprints inaccurately segmented from the flat, multi-finger image acquired by one of the automated collection systems increasing in availability and usage. In such cases, the lost fingerprint can be recovered by re-segmentation from the now compressed multi-finger image record. The second FBI-sponsored tool, CropCoeff was developed by MITRE and thoroughly tested via NIST. CropCoeff enables cropping of the replacement single print directly from the compressed data file, thus avoiding decompression and recompression of images that might degrade fingerprint features necessary for matching.

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

NASA Technical Reports Server (NTRS)

Thompson, David E.; Lindsey, Antonia Edward

2017-01-01

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Performance of Kiestra Total Laboratory Automation Combined with MS in Clinical Microbiology Practice

PubMed Central

Hodiamont, Caspar J.; de Jong, Menno D.; Overmeijer, Hendri P. J.; van den Boogaard, Mandy; Visser, Caroline E.

2014-01-01

Background Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This fully automated sample processing system, equipped with digital imaging technology, allows superior detection of microbial growth. Combining this approach with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) (Bruker Daltonik, Germany) is expected to enable more rapid identification of pathogens. Methods Early growth detection by digital imaging using Kiestra TLA combined with MS was compared to conventional methods (CM) of detection. Accuracy and time taken for microbial identification were evaluated for the two methods in 219 clinical blood culture isolates. The possible clinical impact of earlier microbial identification was assessed according to antibiotic treatment prescription. Results Pathogen identification using Kiestra TLA combined with MS resulted in a 30.6 hr time gain per isolate compared to CM. Pathogens were successfully identified in 98.4% (249/253) of all tested isolates. Early microbial identification without susceptibility testing led to an adjustment of antibiotic regimen in 12% (24/200) of patients. Conclusions The requisite 24 hr incubation time for microbial pathogens to reach sufficient growth for susceptibility testing and identification would be shortened by the implementation of Kiestra TLA in combination with MS, compared to the use of CM. Not only can this method optimize workflow and reduce costs, but it can allow potentially life-saving switches in antibiotic regimen to be initiated sooner. PMID:24624346

Hyperspectral imaging for food processing automation

NASA Astrophysics Data System (ADS)

Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Smith, Doug P.; Feldner, Peggy W.

2002-11-01

This paper presents the research results that demonstrates hyperspectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses, and potential application for real-time, on-line processing of poultry for automatic safety inspection. The hyperspectral imaging system included a line scan camera with prism-grating-prism spectrograph, fiber optic line lighting, motorized lens control, and hyperspectral image processing software. Hyperspectral image processing algorithms, specifically band ratio of dual-wavelength (565/517) images and thresholding were effective on the identification of fecal and ingesta contamination of poultry carcasses. A multispectral imaging system including a common aperture camera with three optical trim filters (515.4 nm with 8.6- nm FWHM), 566.4 nm with 8.8-nm FWHM, and 631 nm with 10.2-nm FWHM), which were selected and validated by a hyperspectral imaging system, was developed for a real-time, on-line application. A total image processing time required to perform the current multispectral images captured by a common aperture camera was approximately 251 msec or 3.99 frames/sec. A preliminary test shows that the accuracy of real-time multispectral imaging system to detect feces and ingesta on corn/soybean fed poultry carcasses was 96%. However, many false positive spots that cause system errors were also detected.

A Fisheries Application of a Dual-Frequency Identification Sonar Acoustic Camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moursund, Russell A.; Carlson, Thomas J.; Peters, Rock D.

2003-06-01

The uses of an acoustic camera in fish passage research at hydropower facilities are being explored by the U.S. Army Corps of Engineers. The Dual-Frequency Identification Sonar (DIDSON) is a high-resolution imaging sonar that obtains near video-quality images for the identification of objects underwater. Developed originally for the Navy by the University of Washington?s Applied Physics Laboratory, it bridges the gap between existing fisheries assessment sonar and optical systems. Traditional fisheries assessment sonars detect targets at long ranges but cannot record the shape of targets. The images within 12 m of this acoustic camera are so clear that one canmore » see fish undulating as they swim and can tell the head from the tail in otherwise zero-visibility water. In the 1.8 MHz high-frequency mode, this system is composed of 96 beams over a 29-degree field of view. This high resolution and a fast frame rate allow the acoustic camera to produce near video-quality images of objects through time. This technology redefines many of the traditional limitations of sonar for fisheries and aquatic ecology. Images can be taken of fish in confined spaces, close to structural or surface boundaries, and in the presence of entrained air. The targets themselves can be visualized in real time. The DIDSON can be used where conventional underwater cameras would be limited in sampling range to < 1 m by low light levels and high turbidity, and where traditional sonar would be limited by the confined sample volume. Results of recent testing at The Dalles Dam, on the lower Columbia River in Oregon, USA, are shown.« less

Solid oxide fuel cell anode image segmentation based on a novel quantum-inspired fuzzy clustering

NASA Astrophysics Data System (ADS)

Fu, Xiaowei; Xiang, Yuhan; Chen, Li; Xu, Xin; Li, Xi

2015-12-01

High quality microstructure modeling can optimize the design of fuel cells. For three-phase accurate identification of Solid Oxide Fuel Cell (SOFC) microstructure, this paper proposes a novel image segmentation method on YSZ/Ni anode Optical Microscopic (OM) images. According to Quantum Signal Processing (QSP), the proposed approach exploits a quantum-inspired adaptive fuzziness factor to adaptively estimate the energy function in the fuzzy system based on Markov Random Filed (MRF). Before defuzzification, a quantum-inspired probability distribution based on distance and gray correction is proposed, which can adaptively adjust the inaccurate probability estimation of uncertain points caused by noises and edge points. In this study, the proposed method improves accuracy and effectiveness of three-phase identification on the micro-investigation. It provides firm foundation to investigate the microstructural evolution and its related properties.

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Identification and quantification of pathogenic helminth eggs using a digital image system.

PubMed

Jiménez, B; Maya, C; Velásquez, G; Torner, F; Arambula, F; Barrios, J A; Velasco, M

2016-07-01

A system was developed to identify and quantify up to seven species of helminth eggs (Ascaris lumbricoides -fertile and unfertile eggs-, Trichuris trichiura, Toxocara canis, Taenia saginata, Hymenolepis nana, Hymenolepis diminuta, and Schistosoma mansoni) in wastewater using different image processing tools and pattern recognition algorithms. The system was developed in three stages. Version one was used to explore the viability of the concept of identifying helminth eggs through an image processing system, while versions 2 and 3 were used to improve its efficiency. The system development was based on the analysis of different properties of helminth eggs in order to discriminate them from other objects in samples processed using the conventional United States Environmental Protection Agency (US EPA) technique to quantify helminth eggs. The system was tested, in its three stages, considering two parameters: specificity (capacity to discriminate between species of helminth eggs and other objects) and sensitivity (capacity to correctly classify and identify the different species of helminth eggs). The final version showed a specificity of 99% while the sensitivity varied between 80 and 90%, depending on the total suspended solids content of the wastewater samples. To achieve such values in samples with total suspended solids (TSS) above 150 mg/L, it is recommended to dilute the concentrated sediment just before taking the images under the microscope. The system allows the helminth eggs most commonly found in wastewater to be reliably and uniformly detected and quantified. In addition, it provides the total number of eggs as well as the individual number by species, and for Ascaris lumbricoides it differentiates whether or not the egg is fertile. The system only requires basically trained technicians to prepare the samples, as for visual identification there is no need for highly trained personnel. The time required to analyze each image is less than a minute. This system could be used in central analytical laboratories providing a remote analysis service. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

ManPortable and UGV LIVAR: advances in sensor suite integration bring improvements to target observation and identification for the electronic battlefield

NASA Astrophysics Data System (ADS)

Lynam, Jeff R.

2001-09-01

A more highly integrated, electro-optical sensor suite using Laser Illuminated Viewing and Ranging (LIVAR) techniques is being developed under the Army Advanced Concept Technology- II (ACT-II) program for enhanced manportable target surveillance and identification. The ManPortable LIVAR system currently in development employs a wide-array of sensor technologies that provides the foot-bound soldier and UGV significant advantages and capabilities in lightweight, fieldable, target location, ranging and imaging systems. The unit incorporates a wide field-of-view, 5DEG x 3DEG, uncooled LWIR passive sensor for primary target location. Laser range finding and active illumination is done with a triggered, flash-lamp pumped, eyesafe micro-laser operating in the 1.5 micron region, and is used in conjunction with a range-gated, electron-bombarded CCD digital camera to then image the target objective in a more- narrow, 0.3$DEG, field-of-view. Target range determination is acquired using the integrated LRF and a target position is calculated using data from other onboard devices providing GPS coordinates, tilt, bank and corrected magnetic azimuth. Range gate timing and coordinated receiver optics focus control allow for target imaging operations to be optimized. The onboard control electronics provide power efficient, system operations for extended field use periods from the internal, rechargeable battery packs. Image data storage, transmission, and processing performance capabilities are also being incorporated to provide the best all-around support, for the electronic battlefield, in this type of system. The paper will describe flash laser illumination technology, EBCCD camera technology with flash laser detection system, and image resolution improvement through frame averaging.

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

PubMed

Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N

2015-06-01

Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for detecting the laminae and facet joints in ultrasound images has been proposed. The system has the potential to assist the anesthesiologists in quickly finding the target plane for epidural steroid injections and facet joint injections.

A theory of fine structure image models with an application to detection and classification of dementia

PubMed Central

Penn, Richard; Werner, Michael; Thomas, Justin

2015-01-01

Background Estimation of stochastic process models from data is a common application of time series analysis methods. Such system identification processes are often cast as hypothesis testing exercises whose intent is to estimate model parameters and test them for statistical significance. Ordinary least squares (OLS) regression and the Levenberg-Marquardt algorithm (LMA) have proven invaluable computational tools for models being described by non-homogeneous, linear, stationary, ordinary differential equations. Methods In this paper we extend stochastic model identification to linear, stationary, partial differential equations in two independent variables (2D) and show that OLS and LMA apply equally well to these systems. The method employs an original nonparametric statistic as a test for the significance of estimated parameters. Results We show gray scale and color images are special cases of 2D systems satisfying a particular autoregressive partial difference equation which estimates an analogous partial differential equation. Several applications to medical image modeling and classification illustrate the method by correctly classifying demented and normal OLS models of axial magnetic resonance brain scans according to subject Mini Mental State Exam (MMSE) scores. Comparison with 13 image classifiers from the literature indicates our classifier is at least 14 times faster than any of them and has a classification accuracy better than all but one. Conclusions Our modeling method applies to any linear, stationary, partial differential equation and the method is readily extended to 3D whole-organ systems. Further, in addition to being a robust image classifier, estimated image models offer insights into which parameters carry the most diagnostic image information and thereby suggest finer divisions could be made within a class. Image models can be estimated in milliseconds which translate to whole-organ models in seconds; such runtimes could make real-time medicine and surgery modeling possible. PMID:26029638

Standoff imaging of a masked human face using a 670 GHz high resolution radar

NASA Astrophysics Data System (ADS)

Kjellgren, Jan; Svedin, Jan; Cooper, Ken B.

2011-11-01

This paper presents an exploratory attempt to use high-resolution radar measurements for face identification in forensic applications. An imaging radar system developed by JPL was used to measure a human face at 670 GHz. Frontal views of the face were measured both with and without a ski mask at a range of 25 m. The realized spatial resolution was roughly 1 cm in all three dimensions. The surfaces of the ski mask and the face were detected by using the two dominating reflections from amplitude data. Various methods for visualization of these surfaces are presented. The possibility to use radar data to determine certain face distance measures between well-defined face landmarks, typically used for anthropometric statistics, was explored. The measures used here were face length, frontal breadth and interpupillary distance. In many cases the radar system seems to provide sufficient information to exclude an innocent subject from suspicion. For an accurate identification it is believed that a system must provide significantly more information.

Current approaches and future role of high content imaging in safety sciences and drug discovery.

PubMed

van Vliet, Erwin; Daneshian, Mardas; Beilmann, Mario; Davies, Anthony; Fava, Eugenio; Fleck, Roland; Julé, Yvon; Kansy, Manfred; Kustermann, Stefan; Macko, Peter; Mundy, William R; Roth, Adrian; Shah, Imran; Uteng, Marianne; van de Water, Bob; Hartung, Thomas; Leist, Marcel

2014-01-01

High content imaging combines automated microscopy with image analysis approaches to simultaneously quantify multiple phenotypic and/or functional parameters in biological systems. The technology has become an important tool in the fields of safety sciences and drug discovery, because it can be used for mode-of-action identification, determination of hazard potency and the discovery of toxicity targets and biomarkers. In contrast to conventional biochemical endpoints, high content imaging provides insight into the spatial distribution and dynamics of responses in biological systems. This allows the identification of signaling pathways underlying cell defense, adaptation, toxicity and death. Therefore, high content imaging is considered a promising technology to address the challenges for the "Toxicity testing in the 21st century" approach. Currently, high content imaging technologies are frequently applied in academia for mechanistic toxicity studies and in pharmaceutical industry for the ranking and selection of lead drug compounds or to identify/confirm mechanisms underlying effects observed in vivo. A recent workshop gathered scientists working on high content imaging in academia, pharmaceutical industry and regulatory bodies with the objective to compile the state-of-the-art of the technology in the different institutions. Together they defined technical and methodological gaps, proposed quality control measures and performance standards, highlighted cell sources and new readouts and discussed future requirements for regulatory implementation. This review summarizes the discussion, proposed solutions and recommendations of the specialists contributing to the workshop.

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

NASA Astrophysics Data System (ADS)

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.

Structured imaging technique in the gynecologic office for the diagnosis of abnormal uterine bleeding.

PubMed

Dueholm, Margit; Hjorth, Ina Marie D

2017-04-01

The aim in the diagnosis of abnormal uterine bleeding (AUB) is to identify the bleeding cause, which can be classified by the PALM-COEIN (Polyp, Adenomyosis, Leiomyoma, Malignancy (and hyperplasia), Coagulopathy, Ovulatory disorders, Endometrial, Iatrogenic and Not otherwise classified) classification system. In a gynecologic setting, the first step is most often to identify structural abnormalities (PALM causes). Common diagnostic options for the identification of the PALM include ultrasonography, endometrial sampling, and hysteroscopy. These options alone or in combination are sufficient for the diagnosis of most women with AUB. Contrast sonography with saline or gel infusion, three-dimensional ultrasonography, and magnetic resonance imaging may be included. The aim of this article is to describe how a simple structured transvaginal ultrasound can be performed and implemented in the common gynecologic practice to simplify the diagnosis of AUB and determine when additional invasive investigations are required. Structured transvaginal ultrasound for the identification of the most common endometrial and myometrial abnormalities and the most common ultrasound features are described. Moreover, situations where magnetic resonance imaging may be included are described. This article proposes a diagnostic setup in premenopausal women for the classification of AUB according to the PALM-COEIN system. Moreover, a future diagnostic setup for fast-track identification of endometrial cancer in postmenopausal women based on a structured evaluation of the endometrium is described. Copyright © 2016. Published by Elsevier Ltd.

Enhancing security of fingerprints through contextual biometric watermarking.

PubMed

Noore, Afzel; Singh, Richa; Vatsa, Mayank; Houck, Max M

2007-07-04

This paper presents a novel digital watermarking technique using face and demographic text data as multiple watermarks for verifying the chain of custody and protecting the integrity of a fingerprint image. The watermarks are embedded in selected texture regions of a fingerprint image using discrete wavelet transform. Experimental results show that modifications in these locations are visually imperceptible and maintain the minutiae details. The integrity of the fingerprint image is verified through the high matching scores obtained from an automatic fingerprint identification system. There is also a high degree of visual correlation between the embedded images, and the extracted images from the watermarked fingerprint. The degree of similarity is computed using pixel-based metrics and human visual system metrics. The results also show that the proposed watermarked fingerprint and the extracted images are resilient to common attacks such as compression, filtering, and noise.

Artificial intelligence for geologic mapping with imaging spectrometers

NASA Technical Reports Server (NTRS)

Kruse, F. A.

1993-01-01

This project was a three year study at the Center for the Study of Earth from Space (CSES) within the Cooperative Institute for Research in Environmental Science (CIRES) at the University of Colorado, Boulder. The goal of this research was to develop an expert system to allow automated identification of geologic materials based on their spectral characteristics in imaging spectrometer data such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This requirement was dictated by the volume of data produced by imaging spectrometers, which prohibits manual analysis. The research described is based on the development of automated techniques for analysis of imaging spectrometer data that emulate the analytical processes used by a human observer. The research tested the feasibility of such an approach, implemented an operational system, and tested the validity of the results for selected imaging spectrometer data sets.

Academic Radiologist Subspecialty Identification Using a Novel Claims-Based Classification System.

PubMed

Rosenkrantz, Andrew B; Wang, Wenyi; Hughes, Danny R; Ginocchio, Luke A; Rosman, David A; Duszak, Richard

2017-06-01

The objective of the present study is to assess the feasibility of a novel claims-based classification system for payer identification of academic radiologist subspecialties. Using a categorization scheme based on the Neiman Imaging Types of Service (NITOS) system, we mapped the Medicare Part B services billed by all radiologists from 2012 to 2014, assigning them to the following subspecialty categories: abdominal imaging, breast imaging, cardiothoracic imaging, musculoskeletal imaging, nuclear medicine, interventional radiology, and neuroradiology. The percentage of subspecialty work relative value units (RVUs) to total billed work RVUs was calculated for each radiologist nationwide. For radiologists at the top 20 academic departments funded by the National Institutes of Health, those percentages were compared with subspecialties designated on faculty websites. NITOS-based subspecialty assignments were also compared with the only radiologist subspecialty classifications currently recognized by Medicare (i.e., nuclear medicine and interventional radiology). Of 1012 academic radiologists studied, the median percentage of Medicare-billed NITOS-based subspecialty work RVUs matching the subspecialty designated on radiologists' own websites ranged from 71.3% (for nuclear medicine) to 98.9% (for neuroradiology). A NITOS-based work RVU threshold of 50% correctly classified 89.8% of radiologists (5.9% were not mapped to any subspecialty; subspecialty error rate, 4.2%). In contrast, existing Medicare provider codes identified only 46.7% of nuclear medicine physicians and 39.4% of interventional radiologists. Using a framework based on a recently established imaging health services research tool that maps service codes based on imaging modality and body region, Medicare claims data can be used to consistently identify academic radiologists by subspecialty in a manner not possible with the use of existing Medicare physician specialty identifiers. This method may facilitate more appropriate performance metrics for subspecialty academic physicians under emerging value-based payment models.

Lock-in imaging with synchronous digital mirror demodulation

NASA Astrophysics Data System (ADS)

Bush, Michael G.

2010-04-01

Lock-in imaging enables high contrast imaging in adverse conditions by exploiting a modulated light source and homodyne detection. We report results on a patent pending lock-in imaging system fabricated from commercial-off-theshelf parts utilizing standard cameras and a spatial light modulator. By leveraging the capabilities of standard parts we are able to present a low cost, high resolution, high sensitivity camera with applications in search and rescue, friend or foe identification (IFF), and covert surveillance. Different operating modes allow the same instrument to be utilized for dual band multispectral imaging or high dynamic range imaging, increasing the flexibility in different operational settings.

3D in vivo imaging with extended-focus optical coherence microscopy.

PubMed

Chen, Yu; Trinh, Le A; Fingler, Jeff; Fraser, Scott E

2017-11-01

Optical coherence microscopy (OCM) has unique advantages of non-invasive 3D imaging without the need of exogenous labels for studying biological samples. However, the imaging depth of this technique is limited by the tradeoff between the depth of focus (DOF) and high lateral resolution in Gaussian optics. To overcome this limitation, we have developed an extended-focus OCM (xf-OCM) imaging system using quasi-Bessel beam illumination to extend the DOF to ∼100 μm, about 3-fold greater than standard OCM. High lateral resolution of 1.6 μm ensured detailed identification of structures within live animal samples. The insensitivity to spherical aberrations strengthened the capability of our xf-OCM system in 3D biological imaging. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

On-board landmark navigation and attitude reference parallel processor system

NASA Technical Reports Server (NTRS)

Gilbert, L. E.; Mahajan, D. T.

1978-01-01

An approach to autonomous navigation and attitude reference for earth observing spacecraft is described along with the landmark identification technique based on a sequential similarity detection algorithm (SSDA). Laboratory experiments undertaken to determine if better than one pixel accuracy in registration can be achieved consistent with onboard processor timing and capacity constraints are included. The SSDA is implemented using a multi-microprocessor system including synchronization logic and chip library. The data is processed in parallel stages, effectively reducing the time to match the small known image within a larger image as seen by the onboard image system. Shared memory is incorporated in the system to help communicate intermediate results among microprocessors. The functions include finding mean values and summation of absolute differences over the image search area. The hardware is a low power, compact unit suitable to onboard application with the flexibility to provide for different parameters depending upon the environment.

A system for diagnosis of wheat leaf diseases based on Android smartphone

NASA Astrophysics Data System (ADS)

Xie, Xinhua; Zhang, Xiangqian; He, Bing; Liang, Dong; Zhang, Dongyang; Huang, Linsheng

2016-10-01

Owing to the shortages of inconvenience, expensive and high professional requirements etc. for conventional recognition devices of wheat leaf diseases, it does not satisfy the requirements of uploading and releasing timely investigation data in the large-scale field, which may influence the effectiveness of prevention and control for wheat diseases. In this study, a fast, accurate, and robust diagnose system of wheat leaf diseases based on android smartphone was developed, which comprises of two parts—the client and the server. The functions of the client include image acquisition, GPS positioning, corresponding, and knowledge base of disease prevention and control. The server includes image processing, feature extraction, and selection, and classifier establishing. The recognition process of the system goes as follow: when disease images were collected in fields and sent to the server by android smartphone, and then image processing of disease spots was carried out by the server. Eighteen larger weight features were selected by algorithm relief-F and as the input of Relevance Vector Machine (RVM), and the automatic identification of wheat stripe rust and powdery mildew was realized. The experimental results showed that the average recognition rate and predicted speed of RVM model were 5.56% and 7.41 times higher than that of Support Vector Machine (SVM). And application discovered that it needs about 1 minute to get the identification result. Therefore, it can be concluded that the system could be used to recognize wheat diseases and real-time investigate in fields.

Integrating research and clinical neuroimaging for the evaluation of traumatic brain injury recovery

NASA Astrophysics Data System (ADS)

Senseney, Justin; Ollinger, John; Graner, John; Lui, Wei; Oakes, Terry; Riedy, Gerard

2015-03-01

Advanced MRI research and other imaging modalities may serve as biomarkers for the evaluation of traumatic brain injury (TBI) recovery. However, these advanced modalities typically require off-line processing which creates images that are incompatible with radiologist viewing software sold commercially. AGFA Impax is an example of such a picture archiving and communication system(PACS) that is used by many radiology departments in the United States Military Health System. By taking advantage of Impax's use of the Digital Imaging and Communications in Medicine (DICOM) standard, we developed a system that allows for advanced medical imaging to be incorporated into clinical PACS. Radiology research can now be conducted using existing clinical imaging display platforms resources in combination with image processingtechniques that are only available outside of the clinical scanning environment. We extracted the spatial and identification elements of theDICOM standard that are necessary to allow research images to be incorporatedinto a clinical radiology system, and developed a tool that annotates research images with the proper tags. This allows for the evaluation of imaging representations of biological markers that may be useful in theevaluation of TBI and TBI recovery.

A neotropical Miocene pollen database employing image-based search and semantic modeling1

PubMed Central

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

2014-01-01

• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

Study of UV imaging technology for noninvasive detection of latent fingerprints

NASA Astrophysics Data System (ADS)

Li, Hong-xia; Cao, Jing; Niu, Jie-qing; Huang, Yun-gang

2013-09-01

Using UV imaging technology, according to the special absorption 、reflection 、scattering and fluorescence characterization of the various residues in fingerprints (fatty acid ester, protein, and carboxylic acid salts etc) to the UV light, weaken or eliminate the background disturbance to increase the brightness contrast of fingerprints with the background, and design、setup the illumination optical system and UV imaging system, the noninvasive detection of latent fingerprints remaining on various object surface are studied. In the illumination optical system, using the 266nm UV Nd:YAG solid state laser as illumination light source, by calculating the best coupling conditions of the laser beam with UV liquid core fiber and analyzing the beam transforming characterizations, we designed and setup the optical system to realize the UV imaging uniform illumination. In the UV imaging system, the UV lens is selected as the fingerprint imaging element, and the UV intensified CCD (ICCD) which consists of a second-generation UV image intensifier and a CCD coupled by fiber plate and taper directly are used as the imaging sensing element. The best imaging conditions of the UV lens with ICCD were analyzed and the imaging system was designed and setup. In this study, by analyzing the factors which influence the detection effect, optimal design and setup the illumination system and imaging system, latent fingerprints on the surface of the paint tin box、plastic、smooth paper、notebook paper and print paper were noninvasive detected and appeared, and the result meet the fingerprint identification requirements in forensic science.

Raman microspectrometer combined with scattering microscopy and lensless imaging for bacteria identification

NASA Astrophysics Data System (ADS)

Strola, S. A.; Schultz, E.; Allier, C. P.; DesRoches, B.; Lemmonier, J.; Dinten, J.-M.

2013-03-01

In this paper, we report on a compact prototype capable both of lensfree imaging, Raman spectrometry and scattering microscopy from bacteria samples. This instrument allows high-throughput real-time characterization without the need of markers, making it potentially suitable to field label-free biomedical and environmental applications. Samples are illuminated from above with a focused-collimated 532nm laser beam and can be x-y-z scanned. The bacteria detection is based on emerging lensfree imaging technology able to localize cells of interest over a large field-of-view of 24mm2. Raman signal and scattered light are then collected by separate measurement arms simultaneously. In the first arm the emission light is fed by a fiber into a prototype spectrometer, developed by Tornado Spectral System based on Tornado's High Throughput Virtual Slit (HTVS) novel technology. The enhanced light throughput in the spectral region of interest (500-1800 cm-1) reduces Raman acquisition time down to few seconds, thus facilitating experimental protocols and avoiding the bacteria deterioration induced by laser thermal heating. Scattered light impinging in the second arm is collected onto a charge-coupled-device. The reconstructed image allows studying the single bacteria diffraction pattern and their specific structural features. The characterization and identification of different bacteria have been performed to validate and optimize the acquisition system and the component setup. The results obtained demonstrate the benefits of these three techniques combination by providing the precise bacteria localization, their chemical composition and a morphology description. The procedure for a rapid identification of particular pathogen bacteria in a sample is illustrated.

Identification and tracking of vertebrae in ultrasound using deep networks with unsupervised feature learning

NASA Astrophysics Data System (ADS)

Hetherington, Jorden; Pesteie, Mehran; Lessoway, Victoria A.; Abolmaesumi, Purang; Rohling, Robert N.

2017-03-01

Percutaneous needle insertion procedures on the spine often require proper identification of the vertebral level in order to effectively deliver anesthetics and analgesic agents to achieve adequate block. For example, in obstetric epidurals, the target is at the L3-L4 intervertebral space. The current clinical method involves "blind" identification of the vertebral level through manual palpation of the spine, which has only 30% accuracy. This implies the need for better anatomical identification prior to needle insertion. A system is proposed to identify the vertebrae, assigning them to their respective levels, and track them in a standard sequence of ultrasound images, when imaged in the paramedian plane. Machine learning techniques are developed to identify discriminative features of the laminae. In particular, a deep network is trained to automatically learn the anatomical features of the lamina peaks, and classify image patches, for pixel-level classification. The chosen network utilizes multiple connected auto-encoders to learn the anatomy. Pre-processing with ultrasound bone enhancement techniques is done to aid the pixel-level classification performance. Once the lamina are identified, vertebrae are assigned levels and tracked in sequential frames. Experimental results were evaluated against an expert sonographer. Based on data acquired from 15 subjects, vertebrae identification with sensitivity of 95% and precision of 95% was achieved within each frame. Between pairs of subsequently analyzed frames, matches of predicted vertebral level labels were correct in 94% of cases, when compared to matches of manually selected labels

Self-image and ethnic identification in South Africa.

PubMed

Bornman, E

1999-08-01

This study examined the relationship between self-image and ethnic identification among 3 South African groups. Participants included random samples of 347 Afrikaans-speaking Whites, 113 English-speaking Whites, and 466 Blacks in urban Gauteng. Positive and negative self-image were extracted using the Rosenberg Self-Esteem Scale (M. Rosenberg, 1965). Afrikaans-speaking Whites had the most positive self-image and Blacks the most negative self-image. A positive self-image was correlated with stronger ethnic identification among Afrikaans-speaking Whites. The opposite was true for Blacks. This relationship was insignificant among English-speaking Whites. Ambivalence toward ingroup identity was persistently correlated with self-image for all groups.

Night Vision Camera

NASA Technical Reports Server (NTRS)

1996-01-01

PixelVision, Inc. developed the Night Video NV652 Back-illuminated CCD Camera, based on the expertise of a former Jet Propulsion Laboratory employee and a former employee of Scientific Imaging Technologies, Inc. The camera operates without an image intensifier, using back-illuminated and thinned CCD technology to achieve extremely low light level imaging performance. The advantages of PixelVision's system over conventional cameras include greater resolution and better target identification under low light conditions, lower cost and a longer lifetime. It is used commercially for research and aviation.

Writer identification on historical Glagolitic documents

NASA Astrophysics Data System (ADS)

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

2013-12-01

This work aims at automatically identifying scribes of historical Slavonic manuscripts. The quality of the ancient documents is partially degraded by faded-out ink or varying background. The writer identification method used is based on image features, which are described with Scale Invariant Feature Transform (SIFT) features. A visual vocabulary is used for the description of handwriting characteristics, whereby the features are clustered using a Gaussian Mixture Model and employing the Fisher kernel. The writer identification approach is originally designed for grayscale images of modern handwritings. But contrary to modern documents, the historical manuscripts are partially corrupted by background clutter and water stains. As a result, SIFT features are also found on the background. Since the method shows also good results on binarized images of modern handwritings, the approach was additionally applied on binarized images of the ancient writings. Experiments show that this preprocessing step leads to a significant performance increase: The identification rate on binarized images is 98.9%, compared to an identification rate of 87.6% gained on grayscale images.

Operation of a Cartesian Robotic System in a Compact Microscope with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark (Inventor)

2006-01-01

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

Performance evaluation of a dynamic telepathology system (Panoptiq™) in the morphologic assessment of peripheral blood film abnormalities.

PubMed

Goswami, R; Pi, D; Pal, J; Cheng, K; Hudoba De Badyn, M

2015-06-01

The study evaluated the performance of a dynamic imaging telepathology system (Panoptiq(™) ) as a diagnostic aid to the identification of peripheral blood film (PBF) abnormalities. The study assumed a laboratory personnel working in a clinical laboratory were operating the telepathology system to seek diagnostic opinion from an external consulting hematopathologist. The study examined 100 blood films, encompassing 23 different hematological diseases, reactive or normal cases. The study revealed that with real-time image transmission in live scanning mode of operation, the telepathology system was able to aid reviewers in achieving excellent accuracy, that is correct interpretation of morphologic abnormalities obtained in 83/84 of the hematologic diseases and 12/12 of the reactive/normal conditions (Sensitivity: 0.99; Specificity: 1.00). In contrast, when only saved static images in digital capture mode of operation were reviewed remotely, interpretative omissions occurred in 8/84 of the hematologic diseases and 0/12 of the reactive/normal conditions (Sensitivity: 0.91; Specificity: 1.00). It is hypothesized that real-time operator-reviewer communication during live scanning played an important role in the identification of key morphologic abnormalities for review. Our study showed the Panoptiq system can be adopted reliably as a dynamic telepathology tool in aiding community laboratories in the triage of PBF cases for external diagnostic consultation. © 2014 John Wiley & Sons Ltd.

Intraoperative Near-infrared Imaging for Parathyroid Gland Identification by Auto-fluorescence: A Feasibility Study.

PubMed

De Leeuw, Frederic; Breuskin, Ingrid; Abbaci, Muriel; Casiraghi, Odile; Mirghani, Haïtham; Ben Lakhdar, Aïcha; Laplace-Builhé, Corinne; Hartl, Dana

2016-09-01

Parathyroid glands (PGs) can be particularly hard to distinguish from surrounding tissue and thus can be damaged or removed during thyroidectomy. Postoperative hypoparathyroidism is the most common complication after thyroidectomy. Very recently, it has been found that the parathyroid tissue shows near-infrared (NIR) auto-fluorescence which could be used for intraoperative detection, without any use of contrast agents. The work described here presents a histological validation ex vivo of the NIR imaging procedure and evaluates intraoperative PG detection by NIR auto-fluorescence using for the first time to our knowledge a commercially available clinical NIR imaging device. Ex vivo study on resected operative specimens combined with a prospective in vivo study of consecutive patients who underwent total or partial thyroid, or parathyroid surgery at a comprehensive cancer center. During surgery, any tissue suspected to be a potential PG by the surgeon was imaged with the Fluobeam 800 (®) system. NIR imaging was compared to conventional histology (ex vivo) and/or visual identification by the surgeon (in vivo). We have validated NIR auto-fluorescence with an ex vivo study including 28 specimens. Sensitivity and specificity were 94.1 and 80 %, respectively. Intraoperative NIR imaging was performed in 35 patients and 81 parathyroids were identified. In 80/81 cases, the fluorescence signal was subjectively obvious on real-time visualization. We determined that PG fluorescence is 2.93 ± 1.59 times greater than thyroid fluorescence in vivo. Real-time NIR imaging based on parathyroid auto-fluorescence is fast, safe, and non-invasive and shows very encouraging results, for intraoperative parathyroid identification.

Near-infrared fluorescence sentinel lymph node mapping in breast cancer: a multicenter experience

PubMed Central

Verbeek, Floris P.R.; Troyan, Susan L.; Mieog, J. Sven D.; Liefers, Gerrit-Jan; Moffitt, Lorissa A.; Rosenberg, Mireille; Hirshfield-Bartek, Judith; Gioux, Sylvain; van de Velde, Cornelis J.H.; Vahrmeijer, Alexander L.; Frangioni, John V.

2014-01-01

NIR fluorescence imaging using indocyanine green (ICG) has the potential to improve the SLN procedure by facilitating percutaneous and intraoperative identification of lymphatic channels and SLNs. Previous studies suggested that a dose of 0.62 mg (1.6 ml of 0.5 mM) ICG is optimal for SLN mapping in breast cancer. The aim of this study was to evaluate the diagnostic accuracy of near-infrared (NIR) fluorescence for sentinel lymph node (SLN) mapping in breast cancer patients when used in conjunction with conventional techniques. Study subjects were 95 breast cancer patients planning to undergo SLN procedure at either the Dana-Farber/Harvard Cancer Center (Boston, MA, USA) or the Leiden University Medical Center (Leiden, the Netherlands) between July 2010 and January 2013. Subjects underwent the standard-of-care SLN procedure at each institution using 99Technetium-colloid in all subjects and patent blue in 27 (28%) of the subjects. NIR fluorescence-guided SLN detection was performed using the Mini-FLARE imaging system. SLN identification was successful in 94 of 95 subjects (99%) using NIR fluorescence imaging or a combination of both NIR fluorescence imaging and radioactive guidance. In 2 of 95 subjects, radioactive guidance was necessary for initial in vivo identification of SLNs. In 1 of 95 subjects, NIR fluorescence was necessary for initial in vivo identification of SLNs. A total of 177 SLNs (mean = 1.9, range = 1–5) were resected: 100% NIR fluorescent, 88% radioactive, and 78% (of 40 nodes) blue. In 2 of 95 subjects (2.1%), SLNs containing macrometastases were found only by NIR fluorescence, and in 1 patient this led to upstaging to N1. This study demonstrates the safe and accurate application of NIR fluorescence imaging for the identification of SLNs in breast cancer patients, but calls into question what technique should be used as the gold standard in future studies. PMID:24337507

The 2002 NASA Faculty Fellowship Program Research Reports

NASA Technical Reports Server (NTRS)

Bland, J. (Compiler)

2003-01-01

Contents include the following: System Identification of X-33. Neural Network Advanced Ceramic Technology for Space Applications at NASA MSFC. Developing a MATLAB-Based Tool for Visualization and Transformation. Subsurface Stress Fields in Single Crystal (Anisotropic). Contacts Our Space Future: A Challenge to the Conceptual Artist Concept Art for Presentation and Education. Identification and Characterization of Extremophile Microorganisms. Significant to Astrobiology. Mathematical Investigation of Gamma Ray and Neutron. Absorption Grid Patterns for Homeland Defense-Related Fourier Imaging Systems. The Potential of Microwave Radiation for Processing Martian Soil. Fuzzy Logic Trajectory Design and Guidance for Terminal Area.

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

PubMed

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.

Tower testing of a 64W shortwave infrared supercontinuum laser for use as a hyperspectral imaging illuminator

NASA Astrophysics Data System (ADS)

Meola, Joseph; Absi, Anthony; Islam, Mohammed N.; Peterson, Lauren M.; Ke, Kevin; Freeman, Michael J.; Ifaraguerri, Agustin I.

2014-06-01

Hyperspectral imaging systems are currently used for numerous activities related to spectral identification of materials. These passive imaging systems rely on naturally reflected/emitted radiation as the source of the signal. Thermal infrared systems measure radiation emitted from objects in the scene. As such, they can operate at both day and night. However, visible through shortwave infrared systems measure solar illumination reflected from objects. As a result, their use is limited to daytime applications. Omni Sciences has produced high powered broadband shortwave infrared super-continuum laser illuminators. A 64-watt breadboard system was recently packaged and tested at Wright-Patterson Air Force Base to gauge beam quality and to serve as a proof-of-concept for potential use as an illuminator for a hyperspectral receiver. The laser illuminator was placed in a tower and directed along a 1.4km slant path to various target materials with reflected radiation measured with both a broadband camera and a hyperspectral imaging system to gauge performance.

Pc-based car license plate reading

NASA Astrophysics Data System (ADS)

Tanabe, Katsuyoshi; Marubayashi, Eisaku; Kawashima, Harumi; Nakanishi, Tadashi; Shio, Akio

1994-03-01

A PC-based car license plate recognition system has been developed. The system recognizes Chinese characters and Japanese phonetic hiragana characters as well as six digits on Japanese license plates. The system consists of a CCD camera, vehicle sensors, a strobe unit, a monitoring center, and an i486-based PC. The PC includes in its extension slots: a vehicle detector board, a strobe emitter board, and an image grabber board. When a passing vehicle is detected by the vehicle sensors, the strobe emits a pulse of light. The light pulse is synchronized with the time the vehicle image is frozen on an image grabber board. The recognition process is composed of three steps: image thresholding, character region extraction, and matching-based character recognition. The recognition software can handle obscured characters. Experimental results for hundreds of outdoor images showed high recognition performance within relatively short performance times. The results confirmed that the system is applicable to a wide variety of applications such as automatic vehicle identification and travel time measurement.

Monitoring of activated sludge settling ability through image analysis: validation on full-scale wastewater treatment plants.

PubMed

Mesquita, D P; Dias, O; Amaral, A L; Ferreira, E C

2009-04-01

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid-liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.

Evaluation of Lip Prints on Different Supports Using a Batch Image Processing Algorithm and Image Superimposition.

PubMed

Herrera, Lara Maria; Fernandes, Clemente Maia da Silva; Serra, Mônica da Costa

2018-01-01

This study aimed to develop and to assess an algorithm to facilitate lip print visualization, and to digitally analyze lip prints on different supports, by superimposition. It also aimed to classify lip prints according to sex. A batch image processing algorithm was developed, which facilitated the identification and extraction of information about lip grooves. However, it performed better for lip print images with a uniform background. Paper and glass slab allowed more correct identifications than glass and the both sides of compact disks. There was no significant difference between the type of support and the amount of matching structures located in the middle area of the lower lip. There was no evidence of association between types of lip grooves and sex. Lip groove patterns of type III and type I were the most common for both sexes. The development of systems for lip print analysis is necessary, mainly concerning digital methods. © 2017 American Academy of Forensic Sciences.

Vision Algorithm for the Solar Aspect System of the High Energy Replicated Optics to Explore the Sun Mission

NASA Technical Reports Server (NTRS)

Cramer, Alexander Krishnan

2014-01-01

This work covers the design and test of a machine vision algorithm for generating high- accuracy pitch and yaw pointing solutions relative to the sun on a high altitude balloon. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small cross-shaped fiducial markers. Images of this plate taken with an off-the-shelf camera were processed to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an "Average Intersection" method, fiducial detection by a matched filter approach, and identification with an ad-hoc method based on the spacing between fiducials. Performance is verified on real test data where possible, but otherwise uses artificially generated data. Pointing knowledge is ultimately verified to meet the 20 arcsecond requirement.

Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

NASA Technical Reports Server (NTRS)

Walker, Brian; Lu, Thomas; Chao, Tien-Hsin

2012-01-01

We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

PathoSpotter-K: A computational tool for the automatic identification of glomerular lesions in histological images of kidneys

NASA Astrophysics Data System (ADS)

Barros, George O.; Navarro, Brenda; Duarte, Angelo; Dos-Santos, Washington L. C.

2017-04-01

PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and pattern recognition methods to detect proliferative glomerular lesions with an accuracy of 88.3 ± 3.6%. Such performance is only achieved by similar systems if they use images of cell in contexts that are much less complex than the glomerular structure. The results indicate that the approach can be applied to the development of systems designed to train pathology students and to assist pathologists in determining large-scale clinicopathological correlations in morphological research.

Real-time, label-free, intraoperative visualization of peripheral nerves and micro-vasculatures using multimodal optical imaging techniques

PubMed Central

Cha, Jaepyeong; Broch, Aline; Mudge, Scott; Kim, Kihoon; Namgoong, Jung-Man; Oh, Eugene; Kim, Peter

2018-01-01

Accurate, real-time identification and display of critical anatomic structures, such as the nerve and vasculature structures, are critical for reducing complications and improving surgical outcomes. Human vision is frequently limited in clearly distinguishing and contrasting these structures. We present a novel imaging system, which enables noninvasive visualization of critical anatomic structures during surgical dissection. Peripheral nerves are visualized by a snapshot polarimetry that calculates the anisotropic optical properties. Vascular structures, both venous and arterial, are identified and monitored in real-time using a near-infrared laser-speckle-contrast imaging. We evaluate the system by performing in vivo animal studies with qualitative comparison by contrast-agent-aided fluorescence imaging. PMID:29541506

Multipurpose Hyperspectral Imaging System

NASA Technical Reports Server (NTRS)

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.

Navigation surgery for intraoperative sentinel lymph node detection using Indocyanine green (ICG) fluorescence real-time imaging in breast cancer.

PubMed

Toh, U; Iwakuma, N; Mishima, M; Okabe, M; Nakagawa, S; Akagi, Y

2015-09-01

A new sensitive fluorescence imaging system was developed for the real-time identification of sentinel lymph nodes (SLNs) in patients with early breast cancer. The purpose of this study was to evaluate the utility of a color charge-coupled device camera system for the intraoperative detection of SLNs and to determine its clinical efficacy and sensitivity in patients with operable breast cancer. We assessed a total of 168 patients diagnosed with or suspected of having early-stage breast cancer without metastasis in SLNs. The intraoperative detection of SLNs was performed using the conventional Indigo Carmine dye (indigotindisulfonate sodium) technique combined with a new Indocyanine green (ICG) imaging system (HyperEye Medical System: HEMS, MIZUHO IKAKOGYO, Japan) to map SLNs, in which the lymphatic vessels and SLNs were visualized transcutaneously with illuminating ICG fluorescence. Between January 2012 and May 2013, SLNs were successfully identified in all 168 patients (detection rate: 100%). By histopathology, the sensitivity was 93.8% for the detection of the metastatic involvement of SLNs (15 of 16 nodal-positive patients). After a median follow-up of 30.5 months, none of the patients presented with axillary recurrence. These results suggest that the HEMS imaging system is a feasible and effective method for the detection of SLNs in breast cancer. Furthermore, the HEMS device permitted the transcutaneous visualization of lymphatic vessels under light conditions, thus facilitating the identification and detection of SLNs without affecting the surgical procedure, together with a high sensitivity and specificity.

Tooth labeling in cone-beam CT using deep convolutional neural network for forensic identification

NASA Astrophysics Data System (ADS)

Miki, Yuma; Muramatsu, Chisako; Hayashi, Tatsuro; Zhou, Xiangrong; Hara, Takeshi; Katsumata, Akitoshi; Fujita, Hiroshi

2017-03-01

In large disasters, dental record plays an important role in forensic identification. However, filing dental charts for corpses is not an easy task for general dentists. Moreover, it is laborious and time-consuming work in cases of large scale disasters. We have been investigating a tooth labeling method on dental cone-beam CT images for the purpose of automatic filing of dental charts. In our method, individual tooth in CT images are detected and classified into seven tooth types using deep convolutional neural network. We employed the fully convolutional network using AlexNet architecture for detecting each tooth and applied our previous method using regular AlexNet for classifying the detected teeth into 7 tooth types. From 52 CT volumes obtained by two imaging systems, five images each were randomly selected as test data, and the remaining 42 cases were used as training data. The result showed the tooth detection accuracy of 77.4% with the average false detection of 5.8 per image. The result indicates the potential utility of the proposed method for automatic recording of dental information.

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahi-Anwar, M; Lo, P; Kim, H

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifiesmore » the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.« less

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

Novel, in-situ Raman and fluorescence measurement techniques: Imaging using optical waveguides

NASA Astrophysics Data System (ADS)

Carter, Jerry Chance

The following dissertation describes the development of methods for performing standoff and in- situ Raman and fluorescence spectroscopy for chemical imaging and non-imaging analytical applications. The use of Raman spectroscopy for the in- situ identification of crack cocaine and cocaine.HCl using a fiberoptic Raman probe and a portable Raman spectrograph has been demonstrated. We show that the Raman spectra of both forms of cocaine are easily distinguishable from common cutting agents and impurities such as benzocaine and lidocaine. We have also demonstrated the use of Raman spectroscopy for in-situ identification of drugs separated by thin layer chromatography. We have investigated the use of small, transportable, Raman systems for standoff Raman spectroscopy (e.g. <20 m). For this work, acousto-optical (AOTF) and liquid crystal tunable filters (LCTF) are being used both with, and in place of dispersive spectrographs and fixed filtering devices. In addition, we improved the flexibility of the system by the use of a modified holographic fiber-optic probe for light and image collection. A comparison of tunable filter technologies for standoff Raman imaging is discussed along with the merits of image transfer devices using small diameter image guides. A standoff Raman imaging system has been developed that utilizes a unique polymer collection mirror. The techniques used to produce these mirrors make it easy to design low f/# polymer mirrors. The performance of a low f/# polymer mirror system for standoff Raman chemical imaging has been demonstrated and evaluated. We have also demonstrated remote Raman hyperspectral imaging using a dimension-reduction, 2-dimensional (2-D) to 1-dimensional (1-D), fiber optic array. In these studies, a modified holographic fiber-optic probe was combined with the dimension-reduction fiber array for remote Raman imaging. The utility of this setup for standoff Raman imaging is demonstrated by monitoring the polymerization of dibromostyrene. To further demonstrate the utility of in- situ spectral imaging, we have shown that small diameter (350 μm) image guides can be used for in-situ measurements of analyte transport in thin membranes. This has been applied to the measurement of H2O diffusion in Nafion™ membranes using the luminescent compound, [Ru(phen)2dppz] 2+, which is a H2O indicator.

Calculation and simulation of atmospheric refraction effects in maritime environments

NASA Astrophysics Data System (ADS)

Dion, Denis, Jr.; Gardenal, Lionel; Lahaie, P.; Forand, J. Luc

2001-01-01

Near the sea surface, atmospheric refraction and turbulence affect both IR transmission and image quality. This produces an impact on both the detection and classification/identification of targets. With the financial participation of the U.S. Office of Naval Research (ONR), Canada's Defence Research Establishment Valcartier (DREV) is developing PRIME (Propagation Resources In the Maritime Environment), a computer model aimed at describing the overall atmospheric effects on IR imagery systems in the marine surface layer. PRIME can be used as a complement to MODTRAN to compute the effective transmittance in the marine surface layer, taking into account the lens effects caused by refraction. It also provides information on image degradation caused by both refraction and turbulence. This paper reviews the refraction phenomena that take place in the surface layer and discusses their effects on target detection and identification. We then show how PRIME can benefit detection studies and image degradation simulations.

Use of a Passive Reaction Wheel Jitter Isolation System to Meet the Advanced X-Ray Astrophysics Facility Imaging Performance Requirements

NASA Technical Reports Server (NTRS)

Pendergast, Karl J.; Schauwecker, Christopher J.

1998-01-01

Third in the series of NASA great observatories, the Advanced X-Ray Astrophysics Facility (AXAF) is scheduled for launch from the Space Shuttle in November of 1998. Following in the path of the Hubble Space Telescope and the Compton Gamma Ray Observatory, this observatory will image light at X-ray wavelengths, facilitating the detailed study of such phenomena as supernovae and quasars. The AXAF project is sponsored by the Marshall Space Flight Center in Huntsville, Alabama. Because of exacting requirements on the performance of the AXAF optical system, it was necessary to reduce the transmission of reaction wheel jitter disturbances to the observatory. This reduction was accomplished via use of a passive mechanical isolation system to interface the reaction wheels with the spacecraft central structure. In addition to presenting a description of the spacecraft, the isolation system, and the key image quality requirement flowdown, this paper details the analyses performed in support of system-level imaging performance requirement verification. These analyses include the identification of system-level requirement suballocations, quantification of imaging and pointing performance, and formulation of unit-level isolation system transmissibility requirements. Given in comparison to the non-isolated system imaging performance, the results of these analyses clearly illustrate the effectiveness of an innovative reaction wheel passive isolation system.

Development of a Computer-Aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

DTIC Science & Technology

2006-06-01

Hadjiiski, and N. Petrick, "Computerized nipple identification for multiple image analysis in computer-aided diagnosis," Medical Physics 31, 2871...candidates, 3 identification of suspicious objects, 4 feature extraction and analysis, and 5 FP reduc- tion by classification of normal tissue...detection of microcalcifi- cations on digitized mammograms.41 An illustration of a La- placian decomposition tree is shown on the left-hand side of Fig. 4

How semantic category modulates preschool children's visual memory.

PubMed

Giganti, Fiorenza; Viggiano, Maria Pia

2015-01-01

The dynamic interplay between perception and memory has been explored in preschool children by presenting filtered stimuli regarding animals and artifacts. The identification of filtered images was markedly influenced by both prior exposure and the semantic nature of the stimuli. The identification of animals required less physical information than artifacts did. Our results corroborate the notion that the human attention system evolves to reliably develop definite category-specific selection criteria by which living entities are monitored in different ways.

Identification of dynamic load for prosthetic structures.

PubMed

Zhang, Dequan; Han, Xu; Zhang, Zhongpu; Liu, Jie; Jiang, Chao; Yoda, Nobuhiro; Meng, Xianghua; Li, Qing

2017-12-01

Dynamic load exists in numerous biomechanical systems, and its identification signifies a critical issue for characterizing dynamic behaviors and studying biomechanical consequence of the systems. This study aims to identify dynamic load in the dental prosthetic structures, namely, 3-unit implant-supported fixed partial denture (I-FPD) and teeth-supported fixed partial denture. The 3-dimensional finite element models were constructed through specific patient's computerized tomography images. A forward algorithm and regularization technique were developed for identifying dynamic load. To verify the effectiveness of the identification method proposed, the I-FPD and teeth-supported fixed partial denture structures were investigated to determine the dynamic loads. For validating the results of inverse identification, an experimental force-measuring system was developed by using a 3-dimensional piezoelectric transducer to measure the dynamic load in the I-FPD structure in vivo. The computationally identified loads were presented with different noise levels to determine their influence on the identification accuracy. The errors between the measured load and identified counterpart were calculated for evaluating the practical applicability of the proposed procedure in biomechanical engineering. This study is expected to serve as a demonstrative role in identifying dynamic loading in biomedical systems, where a direct in vivo measurement may be rather demanding in some areas of interest clinically. Copyright © 2017 John Wiley & Sons, Ltd.

MIDG-Emerging grid technologies for multi-site preclinical molecular imaging research communities.

PubMed

Lee, Jasper; Documet, Jorge; Liu, Brent; Park, Ryan; Tank, Archana; Huang, H K

2011-03-01

Molecular imaging is the visualization and identification of specific molecules in anatomy for insight into metabolic pathways, tissue consistency, and tracing of solute transport mechanisms. This paper presents the Molecular Imaging Data Grid (MIDG) which utilizes emerging grid technologies in preclinical molecular imaging to facilitate data sharing and discovery between preclinical molecular imaging facilities and their collaborating investigator institutions to expedite translational sciences research. Grid-enabled archiving, management, and distribution of animal-model imaging datasets help preclinical investigators to monitor, access and share their imaging data remotely, and promote preclinical imaging facilities to share published imaging datasets as resources for new investigators. The system architecture of the Molecular Imaging Data Grid is described in a four layer diagram. A data model for preclinical molecular imaging datasets is also presented based on imaging modalities currently used in a molecular imaging center. The MIDG system components and connectivity are presented. And finally, the workflow steps for grid-based archiving, management, and retrieval of preclincial molecular imaging data are described. Initial performance tests of the Molecular Imaging Data Grid system have been conducted at the USC IPILab using dedicated VMware servers. System connectivity, evaluated datasets, and preliminary results are presented. The results show the system's feasibility, limitations, direction of future research. Translational and interdisciplinary research in medicine is increasingly interested in cellular and molecular biology activity at the preclinical levels, utilizing molecular imaging methods on animal models. The task of integrated archiving, management, and distribution of these preclinical molecular imaging datasets at preclinical molecular imaging facilities is challenging due to disparate imaging systems and multiple off-site investigators. A Molecular Imaging Data Grid design, implementation, and initial evaluation is presented to demonstrate the secure and novel data grid solution for sharing preclinical molecular imaging data across the wide-area-network (WAN).

Normal and abnormal tissue identification system and method for medical images such as digital mammograms

NASA Technical Reports Server (NTRS)

Heine, John J. (Inventor); Clarke, Laurence P. (Inventor); Deans, Stanley R. (Inventor); Stauduhar, Richard Paul (Inventor); Cullers, David Kent (Inventor)

2001-01-01

A system and method for analyzing a medical image to determine whether an abnormality is present, for example, in digital mammograms, includes the application of a wavelet expansion to a raw image to obtain subspace images of varying resolution. At least one subspace image is selected that has a resolution commensurate with a desired predetermined detection resolution range. A functional form of a probability distribution function is determined for each selected subspace image, and an optimal statistical normal image region test is determined for each selected subspace image. A threshold level for the probability distribution function is established from the optimal statistical normal image region test for each selected subspace image. A region size comprising at least one sector is defined, and an output image is created that includes a combination of all regions for each selected subspace image. Each region has a first value when the region intensity level is above the threshold and a second value when the region intensity level is below the threshold. This permits the localization of a potential abnormality within the image.

High Resolution Ultrasonic Method for 3D Fingerprint Recognizable Characteristics in Biometrics Identification

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Bakulin, E. Yu.; Maeva, A.; Severin, F.

Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

Hierarchical Segmentation Enhances Diagnostic Imaging

NASA Technical Reports Server (NTRS)

2007-01-01

Bartron Medical Imaging LLC (BMI), of New Haven, Connecticut, gained a nonexclusive license from Goddard Space Flight Center to use the RHSEG software in medical imaging. To manage image data, BMI then licensed two pattern-matching software programs from NASA's Jet Propulsion Laboratory that were used in image analysis and three data-mining and edge-detection programs from Kennedy Space Center. More recently, BMI made NASA history by being the first company to partner with the Space Agency through a Cooperative Research and Development Agreement to develop a 3-D version of RHSEG. With U.S. Food and Drug Administration clearance, BMI will sell its Med-Seg imaging system with the 2-D version of the RHSEG software to analyze medical imagery from CAT and PET scans, MRI, ultrasound, digitized X-rays, digitized mammographies, dental X-rays, soft tissue analyses, moving object analyses, and soft-tissue slides such as Pap smears for the diagnoses and management of diseases. Extending the software's capabilities to three dimensions will eventually enable production of pixel-level views of a tumor or lesion, early identification of plaque build-up in arteries, and identification of density levels of microcalcification in mammographies.

JSC Shuttle Mission Simulator (SMS) visual system payload bay video image

NASA Technical Reports Server (NTRS)

1981-01-01

This video image is of the STS-2 Columbia, Orbiter Vehicle (OV) 102, payload bay (PLB) showing the Office of Space Terrestrial Applications 1 (OSTA-1) pallet (Shuttle Imaging Radar A (SIR-A) antenna (left) and SIR-A recorder, Shuttle Multispectral Infrared Radiometer (SMIRR), Feature Identification Location Experiment (FILE), Measurement of Air Pollution for Satellites (MAPS) (right)). The image is used in JSC's Fixed Based (FB) Shuttle Mission Simulator (SMS). It is projected inside the FB-SMS crew compartment during mission simulation training. The FB-SMS is located in the Mission Simulation and Training Facility Bldg 5.

High performance gel imaging with a commercial single lens reflex camera

NASA Astrophysics Data System (ADS)

Slobodan, J.; Corbett, R.; Wye, N.; Schein, J. E.; Marra, M. A.; Coope, R. J. N.

2011-03-01

A high performance gel imaging system was constructed using a digital single lens reflex camera with epi-illumination to image 19 × 23 cm agarose gels with up to 10,000 DNA bands each. It was found to give equivalent performance to a laser scanner in this high throughput DNA fingerprinting application using the fluorophore SYBR Green®. The specificity and sensitivity of the imager and scanner were within 1% using the same band identification software. Low and high cost color filters were also compared and it was found that with care, good results could be obtained with inexpensive dyed acrylic filters in combination with more costly dielectric interference filters, but that very poor combinations were also possible. Methods for determining resolution, dynamic range, and optical efficiency for imagers are also proposed to facilitate comparison between systems.

Benchmarking image fusion system design parameters

NASA Astrophysics Data System (ADS)

Howell, Christopher L.

2013-06-01

A clear and absolute method for discriminating between image fusion algorithm performances is presented. This method can effectively be used to assist in the design and modeling of image fusion systems. Specifically, it is postulated that quantifying human task performance using image fusion should be benchmarked to whether the fusion algorithm, at a minimum, retained the performance benefit achievable by each independent spectral band being fused. The established benchmark would then clearly represent the threshold that a fusion system should surpass to be considered beneficial to a particular task. A genetic algorithm is employed to characterize the fused system parameters using a Matlab® implementation of NVThermIP as the objective function. By setting the problem up as a mixed-integer constraint optimization problem, one can effectively look backwards through the image acquisition process: optimizing fused system parameters by minimizing the difference between modeled task difficulty measure and the benchmark task difficulty measure. The results of an identification perception experiment are presented, where human observers were asked to identify a standard set of military targets, and used to demonstrate the effectiveness of the benchmarking process.

Visual Recognition Software for Binary Classification and its Application to Pollen Identification

NASA Astrophysics Data System (ADS)

Punyasena, S. W.; Tcheng, D. K.; Nayak, A.

2014-12-01

An underappreciated source of uncertainty in paleoecology is the uncertainty of palynological identifications. The confidence of any given identification is not regularly reported in published results, so cannot be incorporated into subsequent meta-analyses. Automated identifications systems potentially provide a means of objectively measuring the confidence of a given count or single identification, as well as a mechanism for increasing sample sizes and throughput. We developed the software ARLO (Automated Recognition with Layered Optimization) to tackle difficult visual classification problems such as pollen identification. ARLO applies pattern recognition and machine learning to the analysis of pollen images. The features that the system discovers are not the traditional features of pollen morphology. Instead, general purpose image features, such as pixel lines and grids of different dimensions, size, spacing, and resolution, are used. ARLO adapts to a given problem by searching for the most effective combination of feature representation and learning strategy. We present a two phase approach which uses our machine learning process to first segment pollen grains from the background and then classify pollen pixels and report species ratios. We conducted two separate experiments that utilized two distinct sets of algorithms and optimization procedures. The first analysis focused on reconstructing black and white spruce pollen ratios, training and testing our classification model at the slide level. This allowed us to directly compare our automated counts and expert counts to slides of known spruce ratios. Our second analysis focused on maximizing classification accuracy at the individual pollen grain level. Instead of predicting ratios of given slides, we predicted the species represented in a given image window. The resulting analysis was more scalable, as we were able to adapt the most efficient parts of the methodology from our first analysis. ARLO was able to distinguish between the pollen of black and white spruce with an accuracy of ~83.61%. This compared favorably to human expert performance. At the writing of this abstract, we are also experimenting with experimenting with the analysis of higher diversity samples, including modern tropical pollen material collected from ground pollen traps.

[Research Progress on Individual Identification Using Forensic Imaging Data under the Influence of Evidence Rule].

PubMed

Wang, J J; Pei, J C; Qiu, Y L

2016-10-01

With the progress and development of the DNA test and imaging technique, and the evolution of evidence rule which bring the discussions about whether the individual identification using imaging data is outdated, and other disputes such as whether radiologic evidence could be suitable for contemporary evidence and be used to solve the posture difference of imaging test. This article summaries the domestic and foreign researches of individual identification using imaging data in the past 20 years and reviews the problems above. Copyright© by the Editorial Department of Journal of Forensic Medicine.

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

PubMed

Austen, Gail E; Bindemann, Markus; Griffiths, Richard A; Roberts, David L

2018-01-01

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.

Stochastic resonance investigation of object detection in images

NASA Astrophysics Data System (ADS)

Repperger, Daniel W.; Pinkus, Alan R.; Skipper, Julie A.; Schrider, Christina D.

2007-02-01

Object detection in images was conducted using a nonlinear means of improving signal to noise ratio termed "stochastic resonance" (SR). In a recent United States patent application, it was shown that arbitrarily large signal to noise ratio gains could be realized when a signal detection problem is cast within the context of a SR filter. Signal-to-noise ratio measures were investigated. For a binary object recognition task (friendly versus hostile), the method was implemented by perturbing the recognition algorithm and subsequently thresholding via a computer simulation. To fairly test the efficacy of the proposed algorithm, a unique database of images has been constructed by modifying two sample library objects by adjusting their brightness, contrast and relative size via commercial software to gradually compromise their saliency to identification. The key to the use of the SR method is to produce a small perturbation in the identification algorithm and then to threshold the results, thus improving the overall system's ability to discern objects. A background discussion of the SR method is presented. A standard test is proposed in which object identification algorithms could be fairly compared against each other with respect to their relative performance.

Leaf epidermis images for robust identification of plants

PubMed Central

da Silva, Núbia Rosa; Oliveira, Marcos William da Silva; Filho, Humberto Antunes de Almeida; Pinheiro, Luiz Felipe Souza; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2016-01-01

This paper proposes a methodology for plant analysis and identification based on extracting texture features from microscopic images of leaf epidermis. All the experiments were carried out using 32 plant species with 309 epidermal samples captured by an optical microscope coupled to a digital camera. The results of the computational methods using texture features were compared to the conventional approach, where quantitative measurements of stomatal traits (density, length and width) were manually obtained. Epidermis image classification using texture has achieved a success rate of over 96%, while success rate was around 60% for quantitative measurements taken manually. Furthermore, we verified the robustness of our method accounting for natural phenotypic plasticity of stomata, analysing samples from the same species grown in different environments. Texture methods were robust even when considering phenotypic plasticity of stomatal traits with a decrease of 20% in the success rate, as quantitative measurements proved to be fully sensitive with a decrease of 77%. Results from the comparison between the computational approach and the conventional quantitative measurements lead us to discover how computational systems are advantageous and promising in terms of solving problems related to Botany, such as species identification. PMID:27217018

A modular approach to detection and identification of defects in rough lumber

Treesearch

Sang Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

2001-01-01

This paper describes a prototype scanning system that can automatically identify several important defects on rough hardwood lumber. The scanning system utilizes 3 laser sources and an embedded-processor camera to capture and analyze profile and gray-scale images. The modular approach combines the detection of wane (the curved sides of a board, possibly containing...

[Research on identification of cabbages and weeds combining spectral imaging technology and SAM taxonomy].

PubMed

Zu, Qin; Zhang, Shui-fa; Cao, Yang; Zhao, Hui-yi; Dang, Chang-qing

2015-02-01

Weeds automatic identification is the key technique and also the bottleneck for implementation of variable spraying and precision pesticide. Therefore, accurate, rapid and non-destructive automatic identification of weeds has become a very important research direction for precision agriculture. Hyperspectral imaging system was used to capture the hyperspectral images of cabbage seedlings and five kinds of weeds such as pigweed, barnyard grass, goosegrass, crabgrass and setaria with the wavelength ranging from 1000 to 2500 nm. In ENVI, by utilizing the MNF rotation to implement the noise reduction and de-correlation of hyperspectral data and reduce the band dimensions from 256 to 11, and extracting the region of interest to get the spectral library as standard spectra, finally, using the SAM taxonomy to identify cabbages and weeds, the classification effect was good when the spectral angle threshold was set as 0. 1 radians. In HSI Analyzer, after selecting the training pixels to obtain the standard spectrum, the SAM taxonomy was used to distinguish weeds from cabbages. Furthermore, in order to measure the recognition accuracy of weeds quantificationally, the statistical data of the weeds and non-weeds were obtained by comparing the SAM classification image with the best classification effects to the manual classification image. The experimental results demonstrated that, when the parameters were set as 5-point smoothing, 0-order derivative and 7-degree spectral angle, the best classification result was acquired and the recognition rate of weeds, non-weeds and overall samples was 80%, 97.3% and 96.8% respectively. The method that combined the spectral imaging technology and the SAM taxonomy together took full advantage of fusion information of spectrum and image. By applying the spatial classification algorithms to establishing training sets for spectral identification, checking the similarity among spectral vectors in the pixel level, integrating the advantages of spectra and images meanwhile considering their accuracy and rapidity and improving weeds detection range in the full range that could detect weeds between and within crop rows, the above method contributes relevant analysis tools and means to the application field requiring the accurate information of plants in agricultural precision management

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

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

PubMed

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.

Comparing an FPGA to a Cell for an Image Processing Application

NASA Astrophysics Data System (ADS)

Rakvic, Ryan N.; Ngo, Hau; Broussard, Randy P.; Ives, Robert W.

2010-12-01

Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), have provided an exciting opportunity to discover the parallel nature of modern image processing algorithms. On the other hand, PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high performance. In this research project, our aim is to study the differences in performance of a modern image processing algorithm on these two hardware platforms. In particular, Iris Recognition Systems have recently become an attractive identification method because of their extremely high accuracy. Iris matching, a repeatedly executed portion of a modern iris recognition algorithm, is parallelized on an FPGA system and a Cell processor. We demonstrate a 2.5 times speedup of the parallelized algorithm on the FPGA system when compared to a Cell processor-based version.

Biometric identification

NASA Astrophysics Data System (ADS)

Syryamkim, V. I.; Kuznetsov, D. N.; Kuznetsova, A. S.

2018-05-01

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space.

Three-dimensional object recognition based on planar images

NASA Astrophysics Data System (ADS)

Mital, Dinesh P.; Teoh, Eam-Khwang; Au, K. C.; Chng, E. K.

1993-01-01

This paper presents the development and realization of a robotic vision system for the recognition of 3-dimensional (3-D) objects. The system can recognize a single object from among a group of known regular convex polyhedron objects that is constrained to lie on a calibrated flat platform. The approach adopted comprises a series of image processing operations on a single 2-dimensional (2-D) intensity image to derive an image line drawing. Subsequently, a feature matching technique is employed to determine 2-D spatial correspondences of the image line drawing with the model in the database. Besides its identification ability, the system can also provide important position and orientation information of the recognized object. The system was implemented on an IBM-PC AT machine executing at 8 MHz without the 80287 Maths Co-processor. In our overall performance evaluation based on a 600 recognition cycles test, the system demonstrated an accuracy of above 80% with recognition time well within 10 seconds. The recognition time is, however, indirectly dependent on the number of models in the database. The reliability of the system is also affected by illumination conditions which must be clinically controlled as in any industrial robotic vision system.

Police witness identification images: a geometric morphometric analysis.

PubMed

Hayes, Susan; Tullberg, Cameron

2012-11-01

Research into witness identification images typically occurs within the laboratory and involves subjective likeness and recognizability judgments. This study analyzed whether actual witness identification images systematically alter the facial shapes of the suspects described. The shape analysis tool, geometric morphometrics, was applied to 46 homologous facial landmarks displayed on 50 witness identification images and their corresponding arrest photographs, using principal component analysis and multivariate regressions. The results indicate that compared with arrest photographs, witness identification images systematically depict suspects with lowered and medially located eyebrows (p = <0.000001). This was found to occur independently of the Police Artist, and did not occur with composites produced under laboratory conditions. There are several possible explanations for this finding, including any, or all, of the following: The suspect was frowning at the time of the incident, the witness had negative feelings toward the suspect, this is an effect of unfamiliar face processing, the suspect displayed fear at the time of their arrest photograph. © 2012 American Academy of Forensic Sciences.

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

Forensics for flatbed scanners

NASA Astrophysics Data System (ADS)

Gloe, Thomas; Franz, Elke; Winkler, Antje

2007-02-01

Within this article, we investigate possibilities for identifying the origin of images acquired with flatbed scanners. A current method for the identification of digital cameras takes advantage of image sensor noise, strictly speaking, the spatial noise. Since flatbed scanners and digital cameras use similar technologies, the utilization of image sensor noise for identifying the origin of scanned images seems to be possible. As characterization of flatbed scanner noise, we considered array reference patterns and sensor line reference patterns. However, there are particularities of flatbed scanners which we expect to influence the identification. This was confirmed by extensive tests: Identification was possible to a certain degree, but less reliable than digital camera identification. In additional tests, we simulated the influence of flatfielding and down scaling as examples for such particularities of flatbed scanners on digital camera identification. One can conclude from the results achieved so far that identifying flatbed scanners is possible. However, since the analyzed methods are not able to determine the image origin in all cases, further investigations are necessary.

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications.

PubMed

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation.

Automated species-level identification and segmentation of planktonic foraminifera using convolutional neural networks

NASA Astrophysics Data System (ADS)

Marchitto, T. M., Jr.; Mitra, R.; Zhong, B.; Ge, Q.; Kanakiya, B.; Lobaton, E.

2017-12-01

Identification and picking of foraminifera from sediment samples is often a laborious and repetitive task. Previous attempts to automate this process have met with limited success, but we show that recent advances in machine learning can be brought to bear on the problem. As a `proof of concept' we have developed a system that is capable of recognizing six species of extant planktonic foraminifera that are commonly used in paleoceanographic studies. Our pipeline begins with digital photographs taken under 16 different illuminations using an LED ring, which are then fused into a single 3D image. Labeled image sets were used to train various types of image classification algorithms, and performance on unlabeled image sets was measured in terms of precision (whether IDs are correct) and recall (what fraction of the target species are found). We find that Convolutional Neural Network (CNN) approaches achieve precision and recall values between 80 and 90%, which is similar precision and better recall than human expert performance using the same type of photographs. We have also trained a CNN to segment the 3D images into individual chambers and apertures, which can not only improve identification performance but also automate the measurement of foraminifera for morphometric studies. Given that there are only 35 species of extant planktonic foraminifera larger than 150 μm, we suggest that a fully automated characterization of this assemblage is attainable. This is the first step toward the realization of a foram picking robot.

Improving the recognition of fingerprint biometric system using enhanced image fusion

NASA Astrophysics Data System (ADS)

Alsharif, Salim; El-Saba, Aed; Stripathi, Reshma

2010-04-01

Fingerprints recognition systems have been widely used by financial institutions, law enforcement, border control, visa issuing, just to mention few. Biometric identifiers can be counterfeited, but considered more reliable and secure compared to traditional ID cards or personal passwords methods. Fingerprint pattern fusion improves the performance of a fingerprint recognition system in terms of accuracy and security. This paper presents digital enhancement and fusion approaches that improve the biometric of the fingerprint recognition system. It is a two-step approach. In the first step raw fingerprint images are enhanced using high-frequency-emphasis filtering (HFEF). The second step is a simple linear fusion process between the raw images and the HFEF ones. It is shown that the proposed approach increases the verification and identification of the fingerprint biometric recognition system, where any improvement is justified using the correlation performance metrics of the matching algorithm.

Cost effective raspberry pi-based radio frequency identification tagging of mice suitable for automated in vivo imaging.

PubMed

Bolaños, Federico; LeDue, Jeff M; Murphy, Timothy H

2017-01-30

Automation of animal experimentation improves consistency, reduces potential for error while decreasing animal stress and increasing well-being. Radio frequency identification (RFID) tagging can identify individual mice in group housing environments enabling animal-specific tracking of physiological parameters. We describe a simple protocol to radio frequency identification (RFID) tag and detect mice. RFID tags were injected sub-cutaneously after brief isoflurane anesthesia and do not require surgical steps such as suturing or incisions. We employ glass-encapsulated 125kHz tags that can be read within 30.2±2.4mm of the antenna. A raspberry pi single board computer and tag reader enable automated logging and cross platform support is possible through Python. We provide sample software written in Python to provide a flexible and cost effective system for logging the weights of multiple mice in relation to pre-defined targets. The sample software can serve as the basis of any behavioral or physiological task where users will need to identify and track specific animals. Recently, we have applied this system of tagging to automated mouse brain imaging within home-cages. We provide a cost effective solution employing open source software to facilitate adoption in applications such as automated imaging or tracking individual animal weights during tasks where food or water restriction is employed as motivation for a specific behavior. Copyright © 2016 Elsevier B.V. All rights reserved.

In vivo microcirculation imaging of the sub surface fingertip using correlation mapping optical coherence tomography (cmOCT)

NASA Astrophysics Data System (ADS)

Dsouza, Roshan I.; Zam, Azhar; Subhash, Hrebesh M.; Larin, Kirill V.; Leahy, Martin

2013-02-01

We describe a novel application of correlation mapping optical coherence tomography (cmOCT) for sub-surface fingerprint biometric identification. Fingerprint biometrics including automated fingerprint identification systems, are commonly used to recognise the fingerprint, since they constitute simple, effective and valuable physical evidence. Spoofing of biometric fingerprint devices can be easily done because of the limited information obtained from the surface topography. In order to overcome this limitation a potentially more secure source of information is required for biometric identification applications. In this study, we retrieve the microcirculation map of the subsurface fingertip by use of the cmOCT technique. To increase probing depth of the sub surface microcirculation, an optical clearing agent composed of 75% glycerol in aqueous solution was applied topically and kept in contact for 15 min. OCT intensity images were acquired from commercial research grade swept source OCT system (model OCT1300SS, Thorlabs Inc. USA). A 3D OCT scan of the fingertip was acquired over an area of 5x5 mm using 1024x1024 A-scans in approximately 70 s. The resulting volume was then processed using the cmOCT technique with a 7x7 kernel to provide a microcirculation map. We believe these results will demonstrate an enhanced security level over artificial fingertips. To the best of our knowledge, this is the first demonstration of imaging microcirculation map of the subsurface fingertip.

Infrared image enhancement using H(infinity) bounds for surveillance applications.

PubMed

Qidwai, Uvais

2008-08-01

In this paper, two algorithms have been presented to enhance the infrared (IR) images. Using the autoregressive moving average model structure and H(infinity) optimal bounds, the image pixels are mapped from the IR pixel space into normal optical image space, thus enhancing the IR image for improved visual quality. Although H(infinity)-based system identification algorithms are very common now, they are not quite suitable for real-time applications owing to their complexity. However, many variants of such algorithms are possible that can overcome this constraint. Two such algorithms have been developed and implemented in this paper. Theoretical and algorithmic results show remarkable enhancement in the acquired images. This will help in enhancing the visual quality of IR images for surveillance applications.

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

NASA Astrophysics Data System (ADS)

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.

GEANT4 simulation of a scintillating-fibre tracker for the cosmic-ray muon tomography of legacy nuclear waste containers

NASA Astrophysics Data System (ADS)

Clarkson, A.; Hamilton, D. J.; Hoek, M.; Ireland, D. G.; Johnstone, J. R.; Kaiser, R.; Keri, T.; Lumsden, S.; Mahon, D. F.; McKinnon, B.; Murray, M.; Nutbeam-Tuffs, S.; Shearer, C.; Staines, C.; Yang, G.; Zimmerman, C.

2014-05-01

Cosmic-ray muons are highly penetrative charged particles that are observed at the sea level with a flux of approximately one per square centimetre per minute. They interact with matter primarily through Coulomb scattering, which is exploited in the field of muon tomography to image shielded objects in a wide range of applications. In this paper, simulation studies are presented that assess the feasibility of a scintillating-fibre tracker system for use in the identification and characterisation of nuclear materials stored within industrial legacy waste containers. A system consisting of a pair of tracking modules above and a pair below the volume to be assayed is simulated within the GEANT4 framework using a range of potential fibre pitches and module separations. Each module comprises two orthogonal planes of fibres that allow the reconstruction of the initial and Coulomb-scattered muon trajectories. A likelihood-based image reconstruction algorithm has been developed that allows the container content to be determined with respect to the scattering density λ, a parameter which is related to the atomic number Z of the scattering material. Images reconstructed from this simulation are presented for a range of anticipated scenarios that highlight the expected image resolution and the potential of this system for the identification of high-Z materials within a shielded, concrete-filled container. First results from a constructed prototype system are presented in comparison with those from a detailed simulation. Excellent agreement between experimental data and simulation is observed showing clear discrimination between the different materials assayed throughout.

Advanced human machine interaction for an image interpretation workstation

NASA Astrophysics Data System (ADS)

Maier, S.; Martin, M.; van de Camp, F.; Peinsipp-Byma, E.; Beyerer, J.

2016-05-01

In recent years, many new interaction technologies have been developed that enhance the usability of computer systems and allow for novel types of interaction. The areas of application for these technologies have mostly been in gaming and entertainment. However, in professional environments, there are especially demanding tasks that would greatly benefit from improved human machine interfaces as well as an overall improved user experience. We, therefore, envisioned and built an image-interpretation-workstation of the future, a multi-monitor workplace comprised of four screens. Each screen is dedicated to a complex software product such as a geo-information system to provide geographic context, an image annotation tool, software to generate standardized reports and a tool to aid in the identification of objects. Using self-developed systems for hand tracking, pointing gestures and head pose estimation in addition to touchscreens, face identification, and speech recognition systems we created a novel approach to this complex task. For example, head pose information is used to save the position of the mouse cursor on the currently focused screen and to restore it as soon as the same screen is focused again while hand gestures allow for intuitive manipulation of 3d objects in mid-air. While the primary focus is on the task of image interpretation, all of the technologies involved provide generic ways of efficiently interacting with a multi-screen setup and could be utilized in other fields as well. In preliminary experiments, we received promising feedback from users in the military and started to tailor the functionality to their needs

Research on the transfer learning of the vehicle logo recognition

NASA Astrophysics Data System (ADS)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

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

PubMed

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 research should focus on other predictors of construed external image and ways to enhance organizational identification. Encouraging the practice of pharmaceutical care may be 1 such way.

Real-time calibration and alignment of the LHCb RICH detectors

NASA Astrophysics Data System (ADS)

HE, Jibo

2017-12-01

In 2015, the LHCb experiment established a new and unique software trigger strategy with the purpose of increasing the purity of the signal events by applying the same algorithms online and offline. To achieve this, real-time calibration and alignment of all LHCb sub-systems is needed to provide vertexing, tracking, and particle identification of the best possible quality. The calibration of the refractive index of the RICH radiators, the calibration of the Hybrid Photon Detector image, and the alignment of the RICH mirror system, are reported in this contribution. The stability of the RICH performance and the particle identification performance are also discussed.

The Sorghum Headworm Calculator: A speedy tool for headworm management

USDA-ARS?s Scientific Manuscript database

The Sorghum Headworm Calculator is an interactive decision support system for sorghum headworm management. It was designed to be easily accessible and usable. It provides users with organized information on identification, sampling, and management using images, descriptions and research-based mana...

Automated determination of dust particles trajectories in the coma of comet 67P

NASA Astrophysics Data System (ADS)

Marín-Yaseli de la Parra, J.; Küppers, M.; Perez Lopez, F.; Besse, S.; Moissl, R.

2017-09-01

During more than two years Rosetta spent at comet 67P, it took thousands of images that contain individual dust particles. To arrive at a statistics of the dust properties, automatic image analysis is required. We present a new methodology for fast-dust identification using a star mask reference system for matching a set of images automatically. The main goal is to derive particle size distributions and to determine if traces of the size distribution of primordial pebbles are still present in today's cometary dust [1].

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

On the effectiveness of noise masks: naturalistic vs. un-naturalistic image statistics.

PubMed

Hansen, Bruce C; Hess, Robert F

2012-05-01

It has been argued that the human visual system is optimized for identification of broadband objects embedded in stimuli possessing orientation averaged power spectra fall-offs that obey the 1/f(β) relationship typically observed in natural scene imagery (i.e., β=2.0 on logarithmic axes). Here, we were interested in whether individual spatial channels leading to recognition are functionally optimized for narrowband targets when masked by noise possessing naturalistic image statistics (β=2.0). The current study therefore explores the impact of variable β noise masks on the identification of narrowband target stimuli ranging in spatial complexity, while simultaneously controlling for physical or perceived differences between the masks. The results show that β=2.0 noise masks produce the largest identification thresholds regardless of target complexity, and thus do not seem to yield functionally optimized channel processing. The differential masking effects are discussed in the context of contrast gain control. Copyright © 2012 Elsevier Ltd. All rights reserved.

SPM for functional identification of individual biomolecules

NASA Astrophysics Data System (ADS)

Ros, Robert; Schwesinger, Falk; Padeste, Celestino; Plueckthun, Andreas; Anselmetti, Dario; Guentherodt, Hans-Joachim; Tiefenauer, Louis

1999-06-01

The identification of specific binding molecules is of increasing interest in the context of drug development based on combinatorial libraries. Scanning Probe Microscopy (SPM) is the method of choice to image and probe individual biomolecules on a surface. Functional identification of biomolecules is a first step towards screening on a single molecule level. As a model system we use recombinant single- chain Fv fragment (scFv) antibody molecules directed against the antigen fluorescein. The scFv's are covalently immobilized on a flat gold surface via the C-terminal cysteine, resulting in a high accessibility of the binding site. The antigen is immobilized covalently via a long hydrophilic spacer to the silicon nitride SPM-tip. This arrangement allows a direct measurement of binding forces. Thus, closely related antibody molecules differing in only one amino acid at their binding site could be distinguished. A novel SPM-software has been developed which combines imaging, force spectroscopic modes, and online analysis. This is a major prerequisite for future screening methods.

Intravital imaging of a pulmonary endothelial surface layer in a murine sepsis model.

PubMed

Park, Inwon; Choe, Kibaek; Seo, Howon; Hwang, Yoonha; Song, Eunjoo; Ahn, Jinhyo; Hwan Jo, You; Kim, Pilhan

2018-05-01

Direct intravital imaging of an endothelial surface layer (ESL) in pulmonary microcirculation could be a valuable approach to investigate the role of a vascular endothelial barrier in various pathological conditions. Despite its importance as a marker of endothelial cell damage and impairment of the vascular system, in vivo visualization of ESL has remained a challenging technical issue. In this work, we implemented a pulmonary microcirculation imaging system integrated to a custom-design video-rate laser scanning confocal microscopy platform. Using the system, a real-time cellular-level microscopic imaging of the lung was successfully performed, which facilitated a clear identification of individual flowing erythrocytes in pulmonary capillaries. Subcellular level pulmonary ESL was identified in vivo by fluorescence angiography using a dextran conjugated fluorophore to label blood plasma and the red blood cell (RBC) exclusion imaging analysis. Degradation of ESL width was directly evaluated in a murine sepsis model in vivo , suggesting an impairment of pulmonary vascular endothelium and endothelial barrier dysfunction.

Intravital imaging of a pulmonary endothelial surface layer in a murine sepsis model

PubMed Central

Park, Inwon; Choe, Kibaek; Seo, Howon; Hwang, Yoonha; Song, Eunjoo; Ahn, Jinhyo; Hwan Jo, You; Kim, Pilhan

2018-01-01

Direct intravital imaging of an endothelial surface layer (ESL) in pulmonary microcirculation could be a valuable approach to investigate the role of a vascular endothelial barrier in various pathological conditions. Despite its importance as a marker of endothelial cell damage and impairment of the vascular system, in vivo visualization of ESL has remained a challenging technical issue. In this work, we implemented a pulmonary microcirculation imaging system integrated to a custom-design video-rate laser scanning confocal microscopy platform. Using the system, a real-time cellular-level microscopic imaging of the lung was successfully performed, which facilitated a clear identification of individual flowing erythrocytes in pulmonary capillaries. Subcellular level pulmonary ESL was identified in vivo by fluorescence angiography using a dextran conjugated fluorophore to label blood plasma and the red blood cell (RBC) exclusion imaging analysis. Degradation of ESL width was directly evaluated in a murine sepsis model in vivo, suggesting an impairment of pulmonary vascular endothelium and endothelial barrier dysfunction. PMID:29760995

Line-scanning Raman imaging spectroscopy for detection of fingerprints.

PubMed

Deng, Sunan; Liu, Le; Liu, Zhiyi; Shen, Zhiyuan; Li, Guohua; He, Yonghong

2012-06-10

Fingerprints are the best form of personal identification for criminal investigation purposes. We present a line-scanning Raman imaging system and use it to detect fingerprints composed of β-carotene and fish oil on different substrates. Although the line-scanning Raman system has been used to map the distribution of materials such as polystyrene spheres and minerals within geological samples, this is the first time to our knowledge that the method is used in imaging fingerprints. Two Raman peaks of β-carotene (501.2, 510.3 nm) are detected and the results demonstrate that both peaks can generate excellent images with little difference between them. The system operates at a spectra resolution of about 0.4 nm and can detect β-carotene signals in petroleum ether solution with the limit of detection of 3.4×10(-9) mol/L. The results show that the line-scanning Raman imaging spectroscopy we have built has a high accuracy and can be used in the detection of latent fingerprints in the future.

Dual multispectral and 3D structured light laparoscope

NASA Astrophysics Data System (ADS)

Clancy, Neil T.; Lin, Jianyu; Arya, Shobhit; Hanna, George B.; Elson, Daniel S.

2015-03-01

Intraoperative feedback on tissue function, such as blood volume and oxygenation would be useful to the surgeon in cases where current clinical practice relies on subjective measures, such as identification of ischaemic bowel or tissue viability during anastomosis formation. Also, tissue surface profiling may be used to detect and identify certain pathologies, as well as diagnosing aspects of tissue health such as gut motility. In this paper a dual modality laparoscopic system is presented that combines multispectral reflectance and 3D surface imaging. White light illumination from a xenon source is detected by a laparoscope-mounted fast filter wheel camera to assemble a multispectral image (MSI) cube. Surface shape is then calculated using a spectrally-encoded structured light (SL) pattern detected by the same camera and triangulated using an active stereo technique. Images of porcine small bowel were acquired during open surgery. Tissue reflectance spectra were acquired and blood volume was calculated at each spatial pixel across the bowel wall and mesentery. SL features were segmented and identified using a `normalised cut' algoritm and the colour vector of each spot. Using the 3D geometry defined by the camera coordinate system the multispectral data could be overlaid onto the surface mesh. Dual MSI and SL imaging has the potential to provide augmented views to the surgeon supplying diagnostic information related to blood supply health and organ function. Future work on this system will include filter optimisation to reduce noise in tissue optical property measurement, and minimise spot identification errors in the SL pattern.

Intelligent dental identification system (IDIS) in forensic medicine.

PubMed

Chomdej, T; Pankaow, W; Choychumroon, S

2006-04-20

This study reports the design and development of the intelligent dental identification system (IDIS), including its efficiency and reliability. Five hundred patients were randomly selected from the Dental Department at Police General Hospital in Thailand to create a population of 3000 known subjects. From the original 500 patients, 100 were randomly selected to create a sample of 1000 unidentifiable subjects (400 subjects with completeness and possible alterations of dental information corresponding to natural occurrences and general dental treatments after the last clinical examination, such as missing teeth, dental caries, dental restorations, and dental prosthetics, 100 subjects with completeness and no alteration of dental information, 500 subjects with incompleteness and no alteration of dental information). Attempts were made to identify the unknown subjects utilizing IDIS. The use of IDIS advanced method resulted in consistent outstanding identification in the range of 82.61-100% with minimal error 0-1.19%. The results of this study indicate that IDIS can be used to support dental identification. It supports not only all types of dentitions: primary, mixed, and permanent but also for incomplete and altered dental information. IDIS is particularly useful in providing the huge quantity and redundancy of related documentation associated with forensic odontology. As a computerized system, IDIS can reduce the time required for identification and store dental digital images with many processing features. Furthermore, IDIS establishes enhancements of documental dental record with odontogram and identification codes, electrical dental record with dental database system, and identification methods and algorithms. IDIS was conceptualized based on the guidelines and standards of the American Board of Forensic Odontology (ABFO) and International Criminal Police Organization (INTERPOL).

An optogenetics- and imaging-assisted simultaneous multiple patch-clamp recording system for decoding complex neural circuits

PubMed Central

Wang, Guangfu; Wyskiel, Daniel R; Yang, Weiguo; Wang, Yiqing; Milbern, Lana C; Lalanne, Txomin; Jiang, Xiaolong; Shen, Ying; Sun, Qian-Quan; Zhu, J Julius

2015-01-01

Deciphering neuronal circuitry is central to understanding brain function and dysfunction, yet it remains a daunting task. To facilitate the dissection of neuronal circuits, a process requiring functional analysis of synaptic connections and morphological identification of interconnected neurons, we present here a method for stable simultaneous octuple patch-clamp recordings. This method allows physiological analysis of synaptic interconnections among 4–8 simultaneously recorded neurons and/or 10–30 sequentially recorded neurons, and it allows anatomical identification of >85% of recorded interneurons and >99% of recorded principal neurons. We describe how to apply the method to rodent tissue slices; however, it can be used on other model organisms. We also describe the latest refinements and optimizations of mechanics, electronics, optics and software programs that are central to the realization of a combined single- and two-photon microscopy–based, optogenetics- and imaging-assisted, stable, simultaneous quadruple–viguple patch-clamp recording system. Setting up the system, from the beginning of instrument assembly and software installation to full operation, can be completed in 3–4 d. PMID:25654757

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

NASA Astrophysics Data System (ADS)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Photo anthropometric variations in Japanese facial features: Establishment of large-sample standard reference data for personal identification using a three-dimensional capture system.

PubMed

Ogawa, Y; Wada, B; Taniguchi, K; Miyasaka, S; Imaizumi, K

2015-12-01

This study clarifies the anthropometric variations of the Japanese face by presenting large-sample population data of photo anthropometric measurements. The measurements can be used as standard reference data for the personal identification of facial images in forensic practices. To this end, three-dimensional (3D) facial images of 1126 Japanese individuals (865 male and 261 female Japanese individuals, aged 19-60 years) were acquired as samples using an already validated 3D capture system, and normative anthropometric analysis was carried out. In this anthropometric analysis, first, anthropological landmarks (22 items, i.e., entocanthion (en), alare (al), cheilion (ch), zygion (zy), gonion (go), sellion (se), gnathion (gn), labrale superius (ls), stomion (sto), labrale inferius (li)) were positioned on each 3D facial image (the direction of which had been adjusted to the Frankfort horizontal plane as the standard position for appropriate anthropometry), and anthropometric absolute measurements (19 items, i.e., bientocanthion breadth (en-en), nose breadth (al-al), mouth breadth (ch-ch), bizygomatic breadth (zy-zy), bigonial breadth (go-go), morphologic face height (se-gn), upper-lip height (ls-sto), lower-lip height (sto-li)) were exported using computer software for the measurement of a 3D digital object. Second, anthropometric indices (21 items, i.e., (se-gn)/(zy-zy), (en-en)/(al-al), (ls-li)/(ch-ch), (ls-sto)/(sto-li)) were calculated from these exported measurements. As a result, basic statistics, such as the mean values, standard deviations, and quartiles, and details of the distributions of these anthropometric results were shown. All of the results except "upper/lower lip ratio (ls-sto)/(sto-li)" were normally distributed. They were acquired as carefully as possible employing a 3D capture system and 3D digital imaging technologies. The sample of images was much larger than any Japanese sample used before for the purpose of personal identification. The measurements will be useful as standard reference data for forensic practices and as material data for future studies in this field. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response

NASA Astrophysics Data System (ADS)

Nikiforov, M. P.; Reukov, V. V.; Thompson, G. L.; Vertegel, A. A.; Guo, S.; Kalinin, S. V.; Jesse, S.

2009-10-01

Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

1.56 Terahertz 2-frames per second standoff imaging

NASA Astrophysics Data System (ADS)

Goyette, Thomas M.; Dickinson, Jason C.; Linden, Kurt J.; Neal, William R.; Joseph, Cecil S.; Gorveatt, William J.; Waldman, Jerry; Giles, Robert; Nixon, William E.

2008-02-01

A Terahertz imaging system intended to demonstrate identification of objects concealed under clothing was designed, assembled, and tested. The system design was based on a 2.5 m standoff distance, with a capability of visualizing a 0.5 m by 0.5 m scene at an image rate of 2 frames per second. The system optical design consisted of a 1.56 THz laser beam, which was raster swept by a dual torsion mirror scanner. The beam was focused onto the scan subject by a stationary 50 cm-diameter focusing mirror. A heterodyne detection technique was used to down convert the backscattered signal. The system demonstrated a 1.5 cm spot resolution. Human subjects were scanned at a frame rate of 2 frames per second. Hidden metal objects were detected under a jacket worn by the human subject. A movie including data and video images was produced in 1.5 minutes scanning a human through 180° of azimuth angle at 0.7° increment.

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

PubMed

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.

FIREX mission requirements document for renewable resources

NASA Technical Reports Server (NTRS)

Carsey, F.; Dixon, T.

1982-01-01

The initial experimental program and mission requirements for a satellite synthetic aperture radar (SAR) system FIREX (Free-Flying Imaging Radar Experiment) for renewable resources is described. The spacecraft SAR is a C-band and L-band VV polarized system operating at two angles of incidence which is designated as a research instrument for crop identification, crop canopy condition assessments, soil moisture condition estimation, forestry type and condition assessments, snow water equivalent and snow wetness assessments, wetland and coastal land type identification and mapping, flood extent mapping, and assessment of drainage characteristics of watersheds for water resources applications. Specific mission design issues such as the preferred incidence angles for vegetation canopy measurements and the utility of a dual frequency (L and C-band) or dual polarization system as compared to the baseline system are addressed.

Finger vein verification system based on sparse representation.

PubMed

Xin, Yang; Liu, Zhi; Zhang, Haixia; Zhang, Hong

2012-09-01

Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

The applicability of holography in forensic identification: a fusion of the traditional optical technique and digital technique.

PubMed

Biwasaka, Hitoshi; Saigusa, Kiyoshi; Aoki, Yasuhiro

2005-03-01

In this study, the applicability of holography in the 3-dimensional recording of forensic objects such as skulls and mandibulae, and the accuracy of the reconstructed 3-D images, were examined. The virtual holographic image, which records the 3-dimensional data of the original object, is visually observed on the other side of the holographic plate, and reproduces the 3-dimensional shape of the object well. Another type of holographic image, the real image, is focused on a frosted glass screen, and cross-sectional images of the object can be observed. When measuring the distances between anatomical reference points using an image-processing software, the average deviations in the holographic images as compared to the actual objects were less than 0.1 mm. Therefore, holography could be useful as a 3-dimensional recording method of forensic objects. Two superimposition systems using holographic images were examined. In the 2D-3D system, the transparent virtual holographic image of an object is directly superimposed onto the digitized photograph of the same object on the LCD monitor. On the other hand, in the video system, the holographic image captured by the CCD camera is superimposed onto the digitized photographic image using a personal computer. We found that the discrepancy between the outlines of the superimposed holographic and photographic dental images using the video system was smaller than that using the 2D-3D system. Holography seemed to perform comparably to the computer graphic system; however, a fusion with the digital technique would expand the utility of holography in superimposition.

Processing system of jaws tomograms for pathology identification and surgical guide modeling

NASA Astrophysics Data System (ADS)

Putrik, M. B.; Lavrentyeva, Yu. E.; Ivanov, V. Yu.

2015-11-01

The aim of the study is to create an image processing system, which allows dentists to find pathological resorption and to build surgical guide surface automatically. X-rays images of jaws from cone beam tomography or spiral computed tomography are the initial data for processing. One patient's examination always includes up to 600 images (or tomograms), that's why the development of processing system for fast automation search of pathologies is necessary. X-rays images can be useful not for only illness diagnostic but for treatment planning too. We have studied the case of dental implantation - for successful surgical manipulations surgical guides are used. We have created a processing system that automatically builds jaw and teeth boundaries on the x-ray image. After this step, obtained teeth boundaries used for surgical guide surface modeling and jaw boundaries limit the area for further pathologies search. Criterion for the presence of pathological resorption zones inside the limited area is based on statistical investigation. After described actions, it is possible to manufacture surgical guide using 3D printer and apply it in surgical operation.

A double-sided microscope to realize whole-ganglion imaging of membrane potential in the medicinal leech

PubMed Central

Wagenaar, Daniel A

2017-01-01

Studies of neuronal network emergence during sensory processing and motor control are greatly facilitated by technologies that allow us to simultaneously record the membrane potential dynamics of a large population of neurons in single cell resolution. To achieve whole-brain recording with the ability to detect both small synaptic potentials and action potentials, we developed a voltage-sensitive dye (VSD) imaging technique based on a double-sided microscope that can image two sides of a nervous system simultaneously. We applied this system to the segmental ganglia of the medicinal leech. Double-sided VSD imaging enabled simultaneous recording of membrane potential events from almost all of the identifiable neurons. Using data obtained from double-sided VSD imaging, we analyzed neuronal dynamics in both sensory processing and generation of behavior and constructed functional maps for identification of neurons contributing to these processes. PMID:28944754

Mobile image based color correction using deblurring

NASA Astrophysics Data System (ADS)

Wang, Yu; Xu, Chang; Boushey, Carol; Zhu, Fengqing; Delp, Edward J.

2015-03-01

Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. The goals of the Technology Assisted Dietary Assessment (TADA) System, developed at Purdue University, is to automatically identify and quantify foods and beverages consumed by utilizing food images acquired with a mobile device. Color correction serves as a critical step to ensure accurate food identification and volume estimation. We make use of a specifically designed color checkerboard (i.e. a fiducial marker) to calibrate the imaging system so that the variations of food appearance under different lighting conditions can be determined. In this paper, we propose an image quality enhancement technique by combining image de-blurring and color correction. The contribution consists of introducing an automatic camera shake removal method using a saliency map and improving the polynomial color correction model using the LMS color space.

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

PubMed

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.

Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

NASA Astrophysics Data System (ADS)

Xie, Yaoqin; Xing, Lei; Gu, Jia; Liu, Wu

2013-06-01

Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.

EOID System Model Validation, Metrics, and Synthetic Clutter Generation

DTIC Science & Technology

2003-09-30

Our long-term goal is to accurately predict the capability of the current generation of laser-based underwater imaging sensors to perform Electro ... Optic Identification (EOID) against relevant targets in a variety of realistic environmental conditions. The models will predict the impact of

Image retrieval for identifying house plants

NASA Astrophysics Data System (ADS)

Kebapci, Hanife; Yanikoglu, Berrin; Unal, Gozde

2010-02-01

We present a content-based image retrieval system for plant identification which is intended for providing users with a simple method to locate information about their house plants. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various well-known color, texture and shape features for this problem, as well as introducing some new ones. The features are extracted from the general plant region that is segmented from the background using the max-flow min-cut technique. Results on a database of 132 different plant images show promise (in about 72% of the queries, the correct plant image is retrieved among the top-15 results).

The Tetracorder user guide: version 4.4

USGS Publications Warehouse

Livo, Keith Eric; Clark, Roger N.

2014-01-01

Imaging spectroscopy mapping software assists in the identification and mapping of materials based on their chemical properties as expressed in spectral measurements of a planet including the solid or liquid surface or atmosphere. Such software can be used to analyze field, aircraft, or spacecraft data; remote sensing datasets; or laboratory spectra. Tetracorder is a set of software algorithms commanded through an expert system to identify materials based on their spectra (Clark and others, 2003). Tetracorder also can be used in traditional remote sensing analyses, because some of the algorithms are a version of a matched filter. Thus, depending on the instructions fed to the Tetracorder system, results can range from simple matched filter output, to spectral feature fitting, to full identification of surface materials (within the limits of the spectral signatures of materials over the spectral range and resolution of the imaging spectroscopy data). A basic understanding of spectroscopy by the user is required for developing an optimum mapping strategy and assessing the results.

Performance analysis of robust road sign identification

NASA Astrophysics Data System (ADS)

Ali, Nursabillilah M.; Mustafah, Y. M.; Rashid, N. K. A. M.

2013-12-01

This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88% and 77% successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98%. The occurrences of all classes are recognized successfully is between 5% and 10% level of occlusions.

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

NASA Astrophysics Data System (ADS)

Bandibas, J. C.; Takarada, S.

2013-12-01

Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images.

PubMed

Schwartzkopf, Wade C; Bovik, Alan C; Evans, Brian L

2005-12-01

Traditional chromosome imaging has been limited to grayscale images, but recently a 5-fluorophore combinatorial labeling technique (M-FISH) was developed wherein each class of chromosomes binds with a different combination of fluorophores. This results in a multispectral image, where each class of chromosomes has distinct spectral components. In this paper, we develop new methods for automatic chromosome identification by exploiting the multispectral information in M-FISH chromosome images and by jointly performing chromosome segmentation and classification. We (1) develop a maximum-likelihood hypothesis test that uses multispectral information, together with conventional criteria, to select the best segmentation possibility; (2) use this likelihood function to combine chromosome segmentation and classification into a robust chromosome identification system; and (3) show that the proposed likelihood function can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies, which can be indicators of radiation damage, cancer, and a wide variety of inherited diseases. We show that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes. We also show that it outperforms past M-FISH classification techniques that do not use segmentation information.

AOTF hyperspectral microscopic imaging for foodborne pathogenic bacteria detection

NASA Astrophysics Data System (ADS)

Park, Bosoon; Lee, Sangdae; Yoon, Seung-Chul; Sundaram, Jaya; Windham, William R.; Hinton, Arthur, Jr.; Lawrence, Kurt C.

2011-06-01

Hyperspectral microscope imaging (HMI) method which provides both spatial and spectral information can be effective for foodborne pathogen detection. The AOTF-based hyperspectral microscope imaging method can be used to characterize spectral properties of biofilm formed by Salmonella enteritidis as well as Escherichia coli. The intensity of spectral imagery and the pattern of spectral distribution varied with system parameters (integration time and gain) of HMI system. The preliminary results demonstrated determination of optimum parameter values of HMI system and the integration time must be no more than 250 ms for quality image acquisition from biofilm formed by S. enteritidis. Among the contiguous spectral imagery between 450 and 800 nm, the intensity of spectral images at 498, 522, 550 and 594 nm were distinctive for biofilm; whereas, the intensity of spectral images at 546 nm was distinctive for E. coli. For more accurate comparison of intensity from spectral images, a calibration protocol, using neutral density filters and multiple exposures, need to be developed to standardize image acquisition. For the identification or classification of unknown food pathogen samples, ground truth regions-of-interest pixels need to be selected for "spectrally pure fingerprints" for the Salmonella and E. coli species.

Imperceptible watermarking for security of fundus images in tele-ophthalmology applications and computer-aided diagnosis of retina diseases.

PubMed

Singh, Anushikha; Dutta, Malay Kishore

2017-12-01

The authentication and integrity verification of medical images is a critical and growing issue for patients in e-health services. Accurate identification of medical images and patient verification is an essential requirement to prevent error in medical diagnosis. The proposed work presents an imperceptible watermarking system to address the security issue of medical fundus images for tele-ophthalmology applications and computer aided automated diagnosis of retinal diseases. In the proposed work, patient identity is embedded in fundus image in singular value decomposition domain with adaptive quantization parameter to maintain perceptual transparency for variety of fundus images like healthy fundus or disease affected image. In the proposed method insertion of watermark in fundus image does not affect the automatic image processing diagnosis of retinal objects & pathologies which ensure uncompromised computer-based diagnosis associated with fundus image. Patient ID is correctly recovered from watermarked fundus image for integrity verification of fundus image at the diagnosis centre. The proposed watermarking system is tested in a comprehensive database of fundus images and results are convincing. results indicate that proposed watermarking method is imperceptible and it does not affect computer vision based automated diagnosis of retinal diseases. Correct recovery of patient ID from watermarked fundus image makes the proposed watermarking system applicable for authentication of fundus images for computer aided diagnosis and Tele-ophthalmology applications. Copyright © 2017 Elsevier B.V. All rights reserved.

The Compact Microimaging Spectrometer (CMIS): A New Tool for In-Situ Planetary Science

NASA Technical Reports Server (NTRS)

Armstrong, J. C.; Sellar, R. G.

2004-01-01

In-situ identification of trace minerals, ices, or organics in planetary samples may be difficult with panchromatic microscopic imagery and spot spectroscopy. The panchromatic imagery acquired by a microscopic imager provides morphological information and albedo, but these are generally insufficient for unambiguous identification. The spatially-averaged spectra acquired by a nonimaging ( point- or spot- ) spectrometer may enable identification of the major components but identification of unknown trace components is difficult at best. With our Compact Micro-Imaging Spectrometer (CMIS), however, we acquire spectroscopic data in an imaging format at microscopic scales. The distinct spectra of individual grains, provided by our approach, make detection and identification possible even for trace components in regolith or heterogeneous samples.

Recent advances in near-infrared fluorescence-guided imaging surgery using indocyanine green.

PubMed

Namikawa, Tsutomu; Sato, Takayuki; Hanazaki, Kazuhiro

2015-12-01

Near-infrared (NIR) fluorescence imaging has better tissue penetration, allowing for the effective rejection of excitation light and detection deep inside organs. Indocyanine green (ICG) generates NIR fluorescence after illumination by an NIR ray, enabling real-time intraoperative visualization of superficial lymphatic channels and vessels transcutaneously. The HyperEye Medical System (HEMS) can simultaneously detect NIR rays under room light to provide color imaging, which enables visualization under bright light. Thus, NIR fluorescence imaging using ICG can provide for excellent diagnostic accuracy in detecting sentinel lymph nodes in cancer and microvascular circulation in various ischemic diseases, to assist us with intraoperative decision making. Including HEMS in this system could further improve the sentinel lymph node mapping and intraoperative identification of blood supply in reconstructive organs and ischemic diseases, making it more attractive than conventional imaging. Moreover, the development of new laparoscopic imaging systems equipped with NIR will allow fluorescence-guided surgery in a minimally invasive setting. Future directions, including the conjugation of NIR fluorophores to target specific cancer markers might be realistic technology with diagnostic and therapeutic benefits.

Electrophoresis gel image processing and analysis using the KODAK 1D software.

PubMed

Pizzonia, J

2001-06-01

The present article reports on the performance of the KODAK 1D Image Analysis Software for the acquisition of information from electrophoresis experiments and highlights the utility of several mathematical functions for subsequent image processing, analysis, and presentation. Digital images of Coomassie-stained polyacrylamide protein gels containing molecular weight standards and ethidium bromide stained agarose gels containing DNA mass standards are acquired using the KODAK Electrophoresis Documentation and Analysis System 290 (EDAS 290). The KODAK 1D software is used to optimize lane and band identification using features such as isomolecular weight lines. Mathematical functions for mass standard representation are presented, and two methods for estimation of unknown band mass are compared. Given the progressive transition of electrophoresis data acquisition and daily reporting in peer-reviewed journals to digital formats ranging from 8-bit systems such as EDAS 290 to more expensive 16-bit systems, the utility of algorithms such as Gaussian modeling, which can correct geometric aberrations such as clipping due to signal saturation common at lower bit depth levels, is discussed. Finally, image-processing tools that can facilitate image preparation for presentation are demonstrated.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-05-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI`s Integrated Automated Fingerprint Identification System.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-01-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI's Integrated Automated Fingerprint Identification System.

Advanced visualization platform for surgical operating room coordination: distributed video board system.

PubMed

Hu, Peter F; Xiao, Yan; Ho, Danny; Mackenzie, Colin F; Hu, Hao; Voigt, Roger; Martz, Douglas

2006-06-01

One of the major challenges for day-of-surgery operating room coordination is accurate and timely situation awareness. Distributed and secure real-time status information is key to addressing these challenges. This article reports on the design and implementation of a passive status monitoring system in a 19-room surgical suite of a major academic medical center. Key design requirements considered included integrated real-time operating room status display, access control, security, and network impact. The system used live operating room video images and patient vital signs obtained through monitors to automatically update events and operating room status. Images were presented on a "need-to-know" basis, and access was controlled by identification badge authorization. The system delivered reliable real-time operating room images and status with acceptable network impact. Operating room status was visualized at 4 separate locations and was used continuously by clinicians and operating room service providers to coordinate operating room activities.

Novel Use of Ultrasound to Teach Reproductive System Physical Examination Skills and Pelvic Anatomy.

PubMed

Parikh, Tejal; Czuzak, Maria; Bui, Naomi; Wildner, Corinna; Koch, Bryna; Leko, Elizabeth; Rappaport, William; Adhikari, Srikar; Gordon, Paul; Gura, Mike; Ellis, Susan

2018-03-01

To determine whether integration of ultrasound (US) into a reproductive system examination clinical skills lab can increase confidence in palpating key reproductive structures during testicular and bimanual pelvic examinations, reduce anxiety about conducting testicular and bimanual pelvic examinations, and improve performance on multiple-choice questions based on structure identification using US images. Second-year medical students enrolled in the Life Cycle preclinical course participated in this cross-sectional study. A single learning activity was developed to pair the teaching of the reproductive system physical examination with the use of US in the clinical skills lab. The evaluation of the teaching session consisted of a pre-post analysis of student self-reported knowledge, confidence, and anxiety. The response rate for the pre survey was 82% (n = 96), and the rate for the post survey was 79% (n = 93). Students' confidence in their ability to identify reproductive system structures on US images increased from pre to post survey. Their confidence in their ability to palpate the epididymis, uterus, and ovary during a physical examination improved, and their anxiety about conducting testicular and bimanual pelvic examinations decreased. Student satisfaction with the session was high. Students' performance on multiple-choice questions based on structure identification using US images was at 96% or higher. Our study findings support the integration of US into a reproductive system examination clinical skills lab. Medical students acquire competency and confidence in reproductive system physical examination skills with US integration. © 2017 by the American Institute of Ultrasound in Medicine.

Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning.

PubMed

Jing, Xiao-Yuan; Zhu, Xiaoke; Wu, Fei; Hu, Ruimin; You, Xinge; Wang, Yunhong; Feng, Hui; Yang, Jing-Yu

2017-03-01

Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high resolution (HR), while probe images are usually low resolution (LR) in the identification scenarios with large variation of illumination, weather, or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD 2 L) approach for SR person re-identification task. With the HR and LR dictionary pair and mapping matrices learned from the features of HR and LR training images, SLD 2 L can convert the features of the LR probe images into HR features. To ensure that the converted features have favorable discriminative capability and the learned dictionaries can well characterize intrinsic feature spaces of the HR and LR images, we design a discriminant term and a low-rank regularization term for SLD 2 L. Moreover, considering that low resolution results in different degrees of loss for different types of visual appearance features, we propose a multi-view SLD 2 L (MVSLD 2 L) approach, which can learn the type-specific dictionary pair and mappings for each type of feature. Experimental results on multiple publicly available data sets demonstrate the effectiveness of our proposed approaches for the SR person re-identification task.

Fast and automatic thermographic material identification for the recycling process

NASA Astrophysics Data System (ADS)

Haferkamp, Heinz; Burmester, Ingo

1998-03-01

Within the framework of the future closed loop recycling process the automatic and economical sorting of plastics is a decisive element. The at the present time available identification and sorting systems are not yet suitable for the sorting of technical plastics since essential demands, as the realization of high recognition reliability and identification rates considering the variety of technical plastics, can not be guaranteed. Therefore the Laser Zentrum Hannover e.V. in cooperation with the Hoerotron GmbH and the Preussag Noell GmbH has carried out investigations on a rapid thermographic and laser-supported material- identification-system for automatic material-sorting- systems. The automatic identification of different engineering plastics coming from electronic or automotive waste is possible. Identification rates up to 10 parts per second are allowed by the effort from fast IR line scanners. The procedure is based on the following principle: within a few milliseconds a spot on the relevant sample is heated by a CO2 laser. The samples different and specific chemical and physical material properties cause different temperature distributions on their surfaces that are measured by a fast IR-linescan system. This 'thermal impulse response' has to be analyzed by means of a computer system. Investigations have shown that it is possible to analyze more than 18 different sorts of plastics at a frequency of 10 Hz. Crucial for the development of such a system is the rapid processing of imaging data, the minimization of interferences caused by oscillating samples geometries, and a wide range of possible additives in plastics in question. One possible application area is sorting of plastics coming from car- and electronic waste recycling.

Hands-Free Image Capture, Data Tagging and Transfer Using Google Glass: A Pilot Study for Improved Wound Care Management

PubMed Central

Aldaz, Gabriel; Shluzas, Lauren Aquino; Pickham, David; Eris, Ozgur; Sadler, Joel; Joshi, Shantanu; Leifer, Larry

2015-01-01

Chronic wounds, including pressure ulcers, compromise the health of 6.5 million Americans and pose an annual estimated burden of $25 billion to the U.S. health care system. When treating chronic wounds, clinicians must use meticulous documentation to determine wound severity and to monitor healing progress over time. Yet, current wound documentation practices using digital photography are often cumbersome and labor intensive. The process of transferring photos into Electronic Medical Records (EMRs) requires many steps and can take several days. Newer smartphone and tablet-based solutions, such as Epic Haiku, have reduced EMR upload time. However, issues still exist involving patient positioning, image-capture technique, and patient identification. In this paper, we present the development and assessment of the SnapCap System for chronic wound photography. Through leveraging the sensor capabilities of Google Glass, SnapCap enables hands-free digital image capture, and the tagging and transfer of images to a patient’s EMR. In a pilot study with wound care nurses at Stanford Hospital (n=16), we (i) examined feature preferences for hands-free digital image capture and documentation, and (ii) compared SnapCap to the state of the art in digital wound care photography, the Epic Haiku application. We used the Wilcoxon Signed-ranks test to evaluate differences in mean ranks between preference options. Preferred hands-free navigation features include barcode scanning for patient identification, Z(15) = -3.873, p < 0.001, r = 0.71, and double-blinking to take photographs, Z(13) = -3.606, p < 0.001, r = 0.71. In the comparison between SnapCap and Epic Haiku, the SnapCap System was preferred for sterile image-capture technique, Z(16) = -3.873, p < 0.001, r = 0.68. Responses were divided with respect to image quality and overall ease of use. The study’s results have contributed to the future implementation of new features aimed at enhancing mobile hands-free digital photography for chronic wound care. PMID:25902061

Automated Steering Control Design by Visual Feedback Approach —System Identification and Control Experiments with a Radio-Controlled Car—

NASA Astrophysics Data System (ADS)

Fujiwara, Yukihiro; Yoshii, Masakazu; Arai, Yasuhito; Adachi, Shuichi

Advanced safety vehicle(ASV)assists drivers’ manipulation to avoid trafic accidents. A variety of researches on automatic driving systems are necessary as an element of ASV. Among them, we focus on visual feedback approach in which the automatic driving system is realized by recognizing road trajectory using image information. The purpose of this paper is to examine the validity of this approach by experiments using a radio-controlled car. First, a practical image processing algorithm to recognize white lines on the road is proposed. Second, a model of the radio-controlled car is built by system identication experiments. Third, an automatic steering control system is designed based on H∞ control theory. Finally, the effectiveness of the designed control system is examined via traveling experiments.

Remote imaging laser-induced breakdown spectroscopy and laser-induced fluorescence spectroscopy using nanosecond pulses from a mobile lidar system.

PubMed

Grönlund, Rasmus; Lundqvist, Mats; Svanberg, Sune

2006-08-01

A mobile lidar system was used in remote imaging laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF) experiments. Also, computer-controlled remote ablation of a chosen area was demonstrated, relevant to cleaning of cultural heritage items. Nanosecond frequency-tripled Nd:YAG laser pulses at 355 nm were employed in experiments with a stand-off distance of 60 meters using pulse energies of up to 170 mJ. By coaxial transmission and common folding of the transmission and reception optical paths using a large computer-controlled mirror, full elemental imaging capability was achieved on composite targets. Different spectral identification algorithms were compared in producing thematic data based on plasma or fluorescence light.

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

Snapshot spectral and polarimetric imaging; target identification with multispectral video

NASA Astrophysics Data System (ADS)

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.

Merging Dietary Assessment with the Adolescent Lifestyle

PubMed Central

Schap, TusaRebecca E; Zhu, Fengqing M; Delp, Edward J; Boushey, Carol J

2013-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera, (e.g., Apple iPhone, Google Nexus One, Apple iPod Touch). Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis, i.e., segmentation, feature extraction, and classification, allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies (FNDDS) to provide a detailed diet analysis for use in epidemiologic or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarizes the system design and the evidence-based development of image-based methods for dietary assessment among children. PMID:23489518

Three-dimensional imaging of artificial fingerprint by optical coherence tomography

NASA Astrophysics Data System (ADS)

Larin, Kirill V.; Cheng, Yezeng

2008-03-01

Fingerprint recognition is one of the popular used methods of biometrics. However, due to the surface topography limitation, fingerprint recognition scanners are easily been spoofed, e.g. using artificial fingerprint dummies. Thus, biometric fingerprint identification devices need to be more accurate and secure to deal with different fraudulent methods including dummy fingerprints. Previously, we demonstrated that Optical Coherence Tomography (OCT) images revealed the presence of the artificial fingerprints (made from different household materials, such as cement and liquid silicone rubber) at all times, while the artificial fingerprints easily spoofed the commercial fingerprint reader. Also we demonstrated that an analysis of the autocorrelation of the OCT images could be used in automatic recognition systems. Here, we exploited the three-dimensional (3D) imaging of the artificial fingerprint by OCT to generate vivid 3D image for both the artificial fingerprint layer and the real fingerprint layer beneath. With the reconstructed 3D image, it could not only point out whether there exists an artificial material, which is intended to spoof the scanner, above the real finger, but also could provide the hacker's fingerprint. The results of these studies suggested that Optical Coherence Tomography could be a powerful real-time noninvasive method for accurate identification of artificial fingerprints real fingerprints as well.

Hybrid Feature Extraction-based Approach for Facial Parts Representation and Recognition

NASA Astrophysics Data System (ADS)

Rouabhia, C.; Tebbikh, H.

2008-06-01

Face recognition is a specialized image processing which has attracted a considerable attention in computer vision. In this article, we develop a new facial recognition system from video sequences images dedicated to person identification whose face is partly occulted. This system is based on a hybrid image feature extraction technique called ACPDL2D (Rouabhia et al. 2007), it combines two-dimensional principal component analysis and two-dimensional linear discriminant analysis with neural network. We performed the feature extraction task on the eyes and the nose images separately then a Multi-Layers Perceptron classifier is used. Compared to the whole face, the results of simulation are in favor of the facial parts in terms of memory capacity and recognition (99.41% for the eyes part, 98.16% for the nose part and 97.25 % for the whole face).

RMB identification based on polarization parameters inversion imaging

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Imaging anatomy of the vestibular and visual systems.

PubMed

Gunny, Roxana; Yousry, Tarek A

2007-02-01

This review will outline the imaging anatomy of the vestibular and visual pathways, using computed tomography and magnetic resonance imaging, with emphasis on the more recent developments in neuroimaging. Technical advances in computed tomography and magnetic resonance imaging, such as the advent of multislice computed tomography and newer magnetic resonance imaging techniques such as T2-weighted magnetic resonance cisternography, have improved the imaging of the vestibular and visual pathways, allowing better visualization of the end organs and peripheral nerves. Higher field strength magnetic resonance imaging is a promising tool, which has been used to evaluate and resolve fine anatomic detail in vitro, as in the labyrinth. Advanced magnetic resonance imaging techniques such as functional magnetic resonance imaging and diffusion tractography have been used to identify cortical areas of activation and associated white matter pathways, and show potential for the future identification of complex neuronal relays involved in integrating these pathways. The assessment of the various components of the vestibular and the visual systems has improved with more detailed research on the imaging anatomy of these systems, the advent of high field magnetic resonance scanners and multislice computerized tomography, and the wider use of specific techniques such as tractography which displays white matter tracts not directly accessible until now.

Rapid detection of bacterial contamination in cell or tissue cultures based on Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bolwien, Carsten; Sulz, Gerd; Becker, Sebastian; Thielecke, Hagen; Mertsching, Heike; Koch, Steffen

2008-02-01

Monitoring the sterility of cell or tissue cultures is an essential task, particularly in the fields of regenerative medicine and tissue engineering when implanting cells into the human body. We present a system based on a commercially available microscope equipped with a microfluidic cell that prepares the particles found in the solution for analysis, a Raman-spectrometer attachment optimized for non-destructive, rapid recording of Raman spectra, and a data acquisition and analysis tool for identification of the particles. In contrast to conventional sterility testing in which samples are incubated over weeks, our system is able to analyze milliliters of supernatant or cell suspension within hours by filtering relevant particles and placing them on a Raman-friendly substrate in the microfluidic cell. Identification of critical particles via microscopic imaging and subsequent image analysis is carried out before micro-Raman analysis of those particles is then carried out with an excitation wavelength of 785 nm. The potential of this setup is demonstrated by results of artificial contamination of samples with a pool of bacteria, fungi, and spores: single-channel spectra of the critical particles are automatically baseline-corrected without using background data and classified via hierarchical cluster analysis, showing great promise for accurate and rapid detection and identification of contaminants.

Developing a knowledge base to support the annotation of ultrasound images of ectopic pregnancy.

PubMed

Dhombres, Ferdinand; Maurice, Paul; Friszer, Stéphanie; Guilbaud, Lucie; Lelong, Nathalie; Khoshnood, Babak; Charlet, Jean; Perrot, Nicolas; Jauniaux, Eric; Jurkovic, Davor; Jouannic, Jean-Marie

2017-01-31

Ectopic pregnancy is a frequent early complication of pregnancy associated with significant rates of morbidly and mortality. The positive diagnosis of this condition is established through transvaginal ultrasound scanning. The timing of diagnosis depends on the operator expertise in identifying the signs of ectopic pregnancy, which varies dramatically among medical staff with heterogeneous training. Developing decision support systems in this context is expected to improve the identification of these signs and subsequently improve the quality of care. In this article, we present a new knowledge base for ectopic pregnancy, and we demonstrate its use on the annotation of clinical images. The knowledge base is supported by an application ontology, which provides the taxonomy, the vocabulary and definitions for 24 types and 81 signs of ectopic pregnancy, 484 anatomical structures and 32 technical elements for image acquisition. The knowledge base provides a sign-centric model of the domain, with the relations of signs to ectopic pregnancy types, anatomical structures and the technical elements. The evaluation of the ontology and knowledge base demonstrated a positive feedback from a panel of 17 medical users. Leveraging these semantic resources, we developed an application for the annotation of ultrasound images. Using this application, 6 operators achieved a precision of 0.83 for the identification of signs in 208 ultrasound images corresponding to 35 clinical cases of ectopic pregnancy. We developed a new ectopic pregnancy knowledge base for the annotation of ultrasound images. The use of this knowledge base for the annotation of ultrasound images of ectopic pregnancy showed promising results from the perspective of clinical decision support system development. Other gynecological disorders and fetal anomalies may benefit from our approach.

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

PubMed Central

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

Method for localizing and isolating an errant process step

DOEpatents

Tobin, Jr., Kenneth W.; Karnowski, Thomas P.; Ferrell, Regina K.

2003-01-01

A method for localizing and isolating an errant process includes the steps of retrieving from a defect image database a selection of images each image having image content similar to image content extracted from a query image depicting a defect, each image in the selection having corresponding defect characterization data. A conditional probability distribution of the defect having occurred in a particular process step is derived from the defect characterization data. A process step as a highest probable source of the defect according to the derived conditional probability distribution is then identified. A method for process step defect identification includes the steps of characterizing anomalies in a product, the anomalies detected by an imaging system. A query image of a product defect is then acquired. A particular characterized anomaly is then correlated with the query image. An errant process step is then associated with the correlated image.

Multi-Touch Tabletop System Using Infrared Image Recognition for User Position Identification.

PubMed

Suto, Shota; Watanabe, Toshiya; Shibusawa, Susumu; Kamada, Masaru

2018-05-14

A tabletop system can facilitate multi-user collaboration in a variety of settings, including small meetings, group work, and education and training exercises. The ability to identify the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve attaching sensors to the table, chairs, or to the users themselves. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system-usability evaluation. Using an inexpensive FTIR touch panel and infrared light, this system picks up the touch areas and the shadow area of the user's hand by an infrared camera to establish an association between the hand and table touch points and estimate the position of the user touching the table. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. The system-usability evaluation revealed that prior learning was easy and that system operations could be easily performed.

Multi-Touch Tabletop System Using Infrared Image Recognition for User Position Identification

PubMed Central

Suto, Shota; Watanabe, Toshiya; Shibusawa, Susumu; Kamada, Masaru

2018-01-01

A tabletop system can facilitate multi-user collaboration in a variety of settings, including small meetings, group work, and education and training exercises. The ability to identify the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve attaching sensors to the table, chairs, or to the users themselves. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system-usability evaluation. Using an inexpensive FTIR touch panel and infrared light, this system picks up the touch areas and the shadow area of the user’s hand by an infrared camera to establish an association between the hand and table touch points and estimate the position of the user touching the table. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. The system-usability evaluation revealed that prior learning was easy and that system operations could be easily performed. PMID:29758006

Intrahospital teleradiology from the emergency room

NASA Astrophysics Data System (ADS)

Fuhrman, Carl R.; Slasky, B. S.; Gur, David; Lattner, Stefanie; Herron, John M.; Plunkett, Michael B.; Towers, Jeffrey D.; Thaete, F. Leland

1993-09-01

Off-hour operations of the modern emergency room presents a challenge to conventional image management systems. To assess the utility of intrahospital teleradiology systems from the emergency room (ER), we installed a high-resolution film digitizer which was interfaced to a central archive and to a workstation at the main reading room. The system was designed to allow for digitization of images as soon as the films were processed. Digitized images were autorouted to both destinations, and digitized images could be laser printed (if desired). Almost real time interpretations of nonselected cases were performed at both locations (conventional film in the ER and a workstation in the main reading room), and an analysis of disagreements was performed. Our results demonstrate that in spite of a `significant' difference in reporting, `clinically significant differences' were found in less than 5% of cases. Folder management issues, preprocessing, image orientation, and setting reasonable lookup tables for display were identified as the main limitations to the systems' routine use in a busy environment. The main limitation of the conventional film was the identification of subtle abnormalities in the bright regions of the film. Once identified on either system (conventional film or soft display), all abnormalities were visible and detectable on both display modalities.

Structural Acoustic UXO Detection and Identification in Marine Environments

DTIC Science & Technology

2016-05-01

BOSS Buried Object Scanning Sonar DVL Doppler Velocity Log EW East/West IMU Inertial Measurement Unit NRL Naval Research Laboratory NSWC-PCD... Inertial Measurement Unit (IMU) to time-delay and coherently sum matched-filtered phase histories from subsurface focal points over a large number of... Measurement Unit (IMU) systems. In our imaging algorithm, the 2D depth image of a target, i.e. one mapped over x and z or y and z, presents the

Millimeter wave sensor requirements for maritime small craft identification

NASA Astrophysics Data System (ADS)

Krapels, Keith; Driggers, Ronald G.; Garcia, Jose; Boettcher, Evelyn; Prather, Dennis; Schuetz, Chrisopher; Samluk, Jesse; Stein, Lee; Kiser, William; Visnansky, Andrew; Grata, Jeremy; Wikner, David; Harris, Russ

2009-09-01

Passive millimeter wave (mmW) imagers have improved in terms of resolution sensitivity and frame rate. Currently, the Office of Naval Research (ONR), along with the US Army Research, Development and Engineering Command, Communications Electronics Research Development and Engineering Center (RDECOM CERDEC) Night Vision and Electronic Sensor Directorate (NVESD), are investigating the current state-of-the-art of mmW imaging systems. The focus of this study was the performance of mmW imaging systems for the task of small watercraft / boat identification field performance. First mmW signatures were collected. This consisted of a set of eight small watercrafts; at 5 different aspects, during the daylight hours over a 48 hour period in the spring of 2008. Target characteristics were measured and characteristic dimension, signatures, and Root Sum Squared of Target's Temperature (RRSΔT) tabulated. Then an eight-alternative, forced choice (8AFC) human perception experiment was developed and conducted at NVESD. The ability of observers to discriminate between small watercraft was quantified. Next, the task difficulty criterion, V50, was quantified by applying this data to NVESD's target acquisition models using the Targeting Task Performance (TTP) metric. These parameters can be used to evaluate sensor field performance for Anti-Terrorism / Force Protection (AT/FP) and navigation tasks for the U.S. Navy, as well as for design and evaluation of imaging passive mmW sensors for both the U.S. Navy and U.S. Coast Guard.

Portable multispectral fluorescence imaging system for food safety applications

NASA Astrophysics Data System (ADS)

Lefcourt, Alan M.; Kim, Moon S.; Chen, Yud-Ren

2004-03-01

Fluorescence can be a sensitive method for detecting food contaminants. Of particular interest is detection of fecal contamination as feces is the source of many pathogenic organisms. Feces generally contain chlorophyll a and related compounds due to ingestion of plant materials, and these compounds can readily be detected using fluorescence techniques. Described is a fluorescence-imaging system consisting primarily of a UV light source, an intensified camera with a six-position filter wheel, and software for controlling the system and automatically analyzing the resulting images. To validate the system, orchard apples artificially contaminated with dairy feces were used in a "hands-on" public demonstration. The contamination sites were easily identified using automated edge detection and threshold detection algorithms. In addition, by applying feces to apples and then washing sets of apples at hourly intervals, it was determined that five h was the minimum contact time that allowed identification of the contamination site after the apples were washed. There are many potential uses for this system, including studying the efficacy of apple washing systems.

Three dimensional identification card and applications

NASA Astrophysics Data System (ADS)

Zhou, Changhe; Wang, Shaoqing; Li, Chao; Li, Hao; Liu, Zhao

2016-10-01

Three dimensional Identification Card, with its three-dimensional personal image displayed and stored for personal identification, is supposed be the advanced version of the present two-dimensional identification card in the future [1]. Three dimensional Identification Card means that there are three-dimensional optical techniques are used, the personal image on ID card is displayed to be three-dimensional, so we can see three dimensional personal face. The ID card also stores the three-dimensional face information in its inside electronics chip, which might be recorded by using two-channel cameras, and it can be displayed in computer as three-dimensional images for personal identification. Three-dimensional ID card might be one interesting direction to update the present two-dimensional card in the future. Three-dimension ID card might be widely used in airport custom, entrance of hotel, school, university, as passport for on-line banking, registration of on-line game, etc...

Biased lineup instructions and face identification from video images.

PubMed

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.

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

PubMed Central

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

2017-01-01

Purpose 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. Methods 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. Results 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). Conclusions 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. PMID:28873173

Face identification with frequency domain matched filtering in mobile environments

NASA Astrophysics Data System (ADS)

Lee, Dong-Su; Woo, Yong-Hyun; Yeom, Seokwon; Kim, Shin-Hwan

2012-06-01

Face identification at a distance is very challenging since captured images are often degraded by blur and noise. Furthermore, the computational resources and memory are often limited in the mobile environments. Thus, it is very challenging to develop a real-time face identification system on the mobile device. This paper discusses face identification based on frequency domain matched filtering in the mobile environments. Face identification is performed by the linear or phase-only matched filter and sequential verification stages. The candidate window regions are decided by the major peaks of the linear or phase-only matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering test, which verify color and shape information of the candidate regions in order to remove false alarms. All algorithms are built on the mobile device using Android platform. The preliminary results show that face identification of East Asian people can be performed successfully in the mobile environments.

Secure fingerprint identification based on structural and microangiographic optical coherence tomography.

PubMed

Liu, Xuan; Zaki, Farzana; Wang, Yahui; Huang, Qiongdan; Mei, Xin; Wang, Jiangjun

2017-03-10

Optical coherence tomography (OCT) allows noncontact acquisition of fingerprints and hence is a highly promising technology in the field of biometrics. OCT can be used to acquire both structural and microangiographic images of fingerprints. Microangiographic OCT derives its contrast from the blood flow in the vasculature of viable skin tissue, and microangiographic fingerprint imaging is inherently immune to fake fingerprint attack. Therefore, dual-modality (structural and microangiographic) OCT imaging of fingerprints will enable more secure acquisition of biometric data, which has not been investigated before. Our study on fingerprint identification based on structural and microangiographic OCT imaging is, we believe, highly innovative. In this study, we performed OCT imaging study for fingerprint acquisition, and demonstrated the capability of dual-modality OCT imaging for the identification of fake fingerprints.

Arrays of Segmented, Tapered Light Guides for Use With Large, Planar Scintillation Detectors

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Vaigneur, Keith; Stolin, Alexander V.; Jaliparthi, Gangadhar

2015-06-01

Metabolic imaging techniques can potentially improve detection and diagnosis of cancer in women with radiodense and/or fibrocystic breasts. Our group has previously developed a high-resolution positron emission tomography imaging and biopsy device (PEM-PET) to detect and guide the biopsy of suspicious breast lesions. Initial testing revealed that the imaging field-of-view (FOV) of the scanner was smaller than the physical size of the detector's active area, which could hinder sampling of breast areas close to the chest wall. The purpose of this work was to utilize segmented, tapered light guides for optically coupling the scintillator arrays to arrays of position-sensitive photomultipliers to increase both the active FOV and identification of individual scintillator elements. Testing of the new system revealed that the optics of these structures made it possible to discern detector elements from the complete active area of the detector face. In the previous system the top and bottom rows and left and right columns were not identifiable. Additionally, use of the new light guides increased the contrast of individual detector elements by up to 129%. Improved element identification led to a spatial resolution increase by approximately 12%. Due to attenuation of light in the light guides the detector energy resolution decreased from 18.5% to 19.1%. Overall, these improvements should increase the field-of-view and spatial resolution of the dedicated breast-PET system.

A New Pulse Pileup Rejection Method Based on Position Shift Identification

NASA Astrophysics Data System (ADS)

Gu, Z.; Prout, D. L.; Taschereau, R.; Bai, B.; Chatziioannou, A. F.

2016-02-01

Pulse pileup events degrade the signal-to-noise ratio (SNR) of nuclear medicine data. When such events occur in multiplexed detectors, they cause spatial misposition, energy spectrum distortion and degraded timing resolution, which leads to image artifacts. Pulse pileup is pronounced in PETbox4, a bench top PET scanner dedicated to high sensitivity and high resolution imaging of mice. In that system, the combination of high absolute sensitivity, long scintillator decay time (BGO) and highly multiplexed electronics lead to a significant fraction of pulse pileup, reached at lower total activity than for comparable instruments. In this manuscript, a new pulse pileup rejection method named position shift rejection (PSR) is introduced. The performance of PSR is compared with a conventional leading edge rejection (LER) method and with no pileup rejection implemented (NoPR). A comprehensive digital pulse library was developed for objective evaluation and optimization of the PSR and LER, in which pulse waveforms were directly recorded from real measurements exactly representing the signals to be processed. Physical measurements including singles event acquisition, peak system sensitivity and NEMA NU-4 image quality phantom were also performed in the PETbox4 system to validate and compare the different pulse pile-up rejection methods. The evaluation of both physical measurements and model pulse trains demonstrated that the new PSR performs more accurate pileup event identification and avoids erroneous rejection of valid events. For the PETbox4 system, this improvement leads to a significant recovery of sensitivity at low count rates, amounting to about 1/4th of the expected true coincidence events, compared to the LER method. Furthermore, with the implementation of PSR, optimal image quality can be achieved near the peak noise equivalent count rate (NECR).

Visualization of subcapsular hepatic malignancy by indocyanine-green fluorescence imaging during laparoscopic hepatectomy.

PubMed

Kudo, Hiroki; Ishizawa, Takeaki; Tani, Keigo; Harada, Nobuhiro; Ichida, Akihiko; Shimizu, Atsushi; Kaneko, Junichi; Aoki, Taku; Sakamoto, Yoshihiro; Sugawara, Yasuhiko; Hasegawa, Kiyoshi; Kokudo, Norihiro

2014-08-01

Although laparoscopic hepatectomy has increasingly been used to treat cancers in the liver, the accuracy of intraoperative diagnosis may be inferior to that of open surgery because the ability to visualize and palpate the liver surface during laparoscopy is relatively limited. Fluorescence imaging has the potential to provide a simple compensatory diagnostic tool for identification of cancers in the liver during laparoscopic hepatectomy. In 17 patients who were to undergo laparoscopic hepatectomy, 0.5 mg/kg body weight of indocyanine green (ICG) was administered intravenously within the 2 weeks prior to surgery. Intraoperatively, a laparoscopic fluorescence imaging system obtained fluorescence images of its surfaces during mobilization of the liver. In all, 16 hepatocellular carcinomas (HCCs) and 16 liver metastases (LMs) were resected. Of these, laparoscopic ICG fluorescence imaging identified 12 HCCs (75%) and 11 LMs (69%) on the liver surfaces distributed over Couinaud's segments 1-8, including the 17 tumors that had not been identified by visual inspections of normal color images. The 23 tumors that were identified by fluorescence imaging were located closer to the liver surfaces than another nine tumors that were not identified by fluorescence imaging (median [range] depth 1 [0-5] vs. 11 [8-30] mm; p < 0.001). Like palpation during open hepatectomy, laparoscopic ICG fluorescence imaging enables real-time identification of subcapsular liver cancers, thus facilitating estimation of the required extent of hepatic mobilization and determination of the location of an appropriate hepatic transection line.

Intraoperative spatial frequency domain diffuse optical tomography with indo-cyanine green (ICG) fluorescence contrast (Conference Presentation)

NASA Astrophysics Data System (ADS)

Chong, Sang Hoon; Parthasarathy, Ashwin B.; Kavuri, Venkaiah C.; Moscatelli, Frank A.; Singhal, Sunil; Yodh, Arjun G.

2017-02-01

Surgical resection is the most effective treatment strategy for solid tumors, but complete removal of the tumor is critical for post-surgical recovery/long-term survival and is dependent on correct identification of the tumor margin and accurate excision of microscopic residual tumor in the surgical field. Fluorescence image guided surgery is an emerging technique that has shown promise for intraoperative location of tumors and tumor margins. Current versions of such intraoperative fluorescence imaging, however, are generally limited to 2D near-surface images, i.e., without information about tumor depth. Here we present an intraoperative fluorescence imaging system for 3D volumetric imaging of tumors; the system uses spatial frequency domain diffuse optical tomography with an analytic inversion reconstruction method. The new instrument can derive depth-sensitive 3D tumor images at depths up to 1 cm, and it employs compact epi-imaging and illumination suitable for the operating room, with quasi-real-time image reconstruction for surgical visualization. We present experimental results with FDA-approved Indocynanine Green using an extensive array of tissue phantoms and in a pilot in-vivo study.

Intellectual system of identification of Arabic graphics

NASA Astrophysics Data System (ADS)

Abdoullayeva, Gulchin G.; Aliyev, Telman A.; Gurbanova, Nazakat G.

2001-08-01

The studies made by using the domain of graphic images allowed creating facilities of the artificial intelligence for letters, letter combinations etc. for various graphics and prints. The work proposes a system of recognition and identification of symbols of the Arabic graphics, which has its own specificity as compared to Latin and Cyrillic ones. The starting stage of the recognition and the identification is coding with further entry of information into a computer. Here the problem of entry is one of the essentials. For entry of a large volume of information in the unit of time a scanner is usually employed. Along with the scanner the authors suggest their elaboration of technical facilities for effective input and coding of the information. For refinement of symbols not identified from the scanner mostly for a small bulk of information the developed coding devices are used directly in the process of writing. The functional design of the software is elaborated on the basis of the heuristic model of the creative activity of a researcher and experts in the description and estimation of states of the weakly formalizable systems on the strength of the methods of identification and of selection of geometric features.

Optical stereo video signal processor

NASA Technical Reports Server (NTRS)

Craig, G. D. (Inventor)

1985-01-01

An otpical video signal processor is described which produces a two-dimensional cross-correlation in real time of images received by a stereo camera system. The optical image of each camera is projected on respective liquid crystal light valves. The images on the liquid crystal valves modulate light produced by an extended light source. This modulated light output becomes the two-dimensional cross-correlation when focused onto a video detector and is a function of the range of a target with respect to the stereo camera. Alternate embodiments utilize the two-dimensional cross-correlation to determine target movement and target identification.

A novel multimodal optical imaging system for early detection of oral cancer

PubMed Central

Malik, Bilal H.; Jabbour, Joey M.; Cheng, Shuna; Cuenca, Rodrigo; Cheng, Yi-Shing Lisa; Wright, John M.; Jo, Javier A.; Maitland, Kristen C.

2015-01-01

Objectives Several imaging techniques have been advocated as clinical adjuncts to improve identification of suspicious oral lesions. However, these have not yet shown superior sensitivity or specificity over conventional oral examination techniques. We developed a multimodal, multi-scale optical imaging system that combines macroscopic biochemical imaging of fluorescence lifetime imaging (FLIM) with subcellular morphologic imaging of reflectance confocal microscopy (RCM) for early detection of oral cancer. We tested our system on excised human oral tissues. Study Design A total of four tissue specimen were imaged. These specimens were diagnosed as one each: clinically normal, oral lichen planus, gingival hyperplasia, and superficially-invasive squamous cell carcinoma (SCC). The optical and fluorescence lifetime properties of each specimen were recorded. Results Both quantitative and qualitative differences between normal, benign and SCC lesions can be resolved with FLIM-RCM imaging. The results demonstrate that an integrated approach based on these two methods can potentially enable rapid screening and evaluation of large areas of oral epithelial tissue. Conclusions Early results from ongoing studies of imaging human oral cavity illustrate the synergistic combination of the two modalities. An adjunct device based on such optical characterization of oral mucosa can potentially be used to detect oral carcinogenesis in early stages. PMID:26725720

Imaging through atmospheric turbulence for laser based C-RAM systems: an analytical approach

NASA Astrophysics Data System (ADS)

Buske, Ivo; Riede, Wolfgang; Zoz, Jürgen

2013-10-01

High Energy Laser weapons (HEL) have unique attributes which distinguish them from limitations of kinetic energy weapons. HEL weapons engagement process typical starts with identifying the target and selecting the aim point on the target through a high magnification telescope. One scenario for such a HEL system is the countermeasure against rockets, artillery or mortar (RAM) objects to protect ships, camps or other infrastructure from terrorist attacks. For target identification and especially to resolve the aim point it is significant to ensure high resolution imaging of RAM objects. During the whole ballistic flight phase the knowledge about the expectable imaging quality is important to estimate and evaluate the countermeasure system performance. Hereby image quality is mainly influenced by unavoidable atmospheric turbulence. Analytical calculations have been taken to analyze and evaluate image quality parameters during an approaching RAM object. In general, Kolmogorov turbulence theory was implemented to determine atmospheric coherence length and isoplanatic angle. The image acquisition is distinguishing between long and short exposure times to characterize tip/tilt image shift and the impact of high order turbulence fluctuations. Two different observer positions are considered to show the influence of the selected sensor site. Furthermore two different turbulence strengths are investigated to point out the effect of climate or weather condition. It is well known that atmospheric turbulence degenerates image sharpness and creates blurred images. Investigations are done to estimate the effectiveness of simple tip/tilt systems or low order adaptive optics for laser based C-RAM systems.

Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite

NASA Astrophysics Data System (ADS)

Ladner, S. D.; Arnone, R.; Casey, B.; Weidemann, A.; Gray, D.; Shulman, I.; Mahoney, K.; Giddings, T.; Shirron, J.

2009-05-01

Current United States Navy Mine-Counter-Measure (MCM) operations primarily use electro-optical identification (EOID) sensors to identify underwater targets after detection via acoustic sensors. These EOID sensors which are based on laser underwater imaging by design work best in "clear" waters and are limited in coastal waters especially with strong optical layers. Optical properties and in particular scattering and absorption play an important role on systems performance. Surface optical properties alone from satellite are not adequate to determine how well a system will perform at depth due to the existence of optical layers. The spatial and temporal characteristics of the 3d optical variability of the coastal waters along with strength and location of subsurface optical layers maximize chances of identifying underwater targets by exploiting optimum sensor deployment. Advanced methods have been developed to fuse the optical measurements from gliders, optical properties from "surface" satellite snapshot and 3-D ocean circulation models to extend the two-dimensional (2-D) surface satellite optical image into a three-dimensional (3-D) optical volume with subsurface optical layers. Modifications were made to an EOID performance model to integrate a 3-D optical volume covering an entire region of interest as input and derive system performance field. These enhancements extend present capability based on glider optics and EOID sensor models to estimate the system's "image quality". This only yields system performance information for a single glider profile location in a very large operational region. Finally, we define the uncertainty of the system performance by coupling the EOID performance model with the 3-D optical volume uncertainties. Knowing the ensemble spread of EOID performance field provides a new and unique capability for tactical decision makers and Navy Operations.

75 FR 67700 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-03

...) images/ templates for identification, and relevant documentation concerning individual's acceptance... Entrance Processing Command, FOIA/PA Officer (J-1/MHR-MS-SS), 2834 Green Bay Road, North Chicago, IL 60064... inquiries to the Commander, U.S. Military Entrance Processing Command, FOIA/PA Officer (J-1/MHR-MS-SS), 2834...

Space transportation system flight 2 OSTA-1 scientific payload data management plan

NASA Technical Reports Server (NTRS)

1981-01-01

The Shuttle Imaging Radar-A (SIR-A), Shuttle Multispectral Infrared Radiometer (SMIRR), Future Identification and Location Experiment (FILE), Measurement of Air Pollution from Satellites (MAPS), Ocean Color Experiment (OCE), the Night/Day Optical Survey of Lightning (NOSL), and the Heflex Bioengineering Test (HBT) experiments are described.

Characterization of Location Discrepancies between Envisat/ERS Ship Detection Reports and AIS Records During MARISS Phase 2 Trials in France

NASA Astrophysics Data System (ADS)

Le Bras, Jean-Yves; Germain, Olivier; Hajduch, Guillaume

2008-01-01

During the first phase of the MARISS [1] project CLShas set-up a near real time vessel monitoring chainbased on its operational system for surveillance ofillegal fishing in the Indian Ocean and integrating the©SARTool software, developed by BOOSTT echnologies.Trials performed in the English Channel in 2006 were presented in ENVISA T Symposium 2007 showing several coupling examples between ENVISAT IS6 data and VMS systems, a comparison by the user to VTMS data, and also raising several perspectives of improvement [2]. This paper focuses on the second phase of the project.As for the first phase, ENVISAT SAR scenes (narrow swath, IS6 submode, HH polarization) were acquired, processed at Level 1b (ASA_IMP products) and provided by Kongsberg Satellite Services (KSAT), and completed by ERS PRI images acquired by ESA stations through Cat-1 mechanism, ENVISAT WS ship detection reports through ESA GSE MARCOAST, and metocean data acquired by CLS.Automatic Identification System (AIS) data were used in addition to VMS and VTMS for ground truth identification of vessels.This paper presents the main results of these trials:• An assessment of new chain capabilities implemented after the first phase, such as the azimuth ambiguity removal function in the new version of SARTool©• The use of GIS to reduce false alarms and assess image geolocation.• The potential interest of combining ERS and ENVISAT data• A characterization of differences between locations reported by satellite radar and automatic identification systems.

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

NASA Astrophysics Data System (ADS)

Liu, Xiyao; Lou, Jieting; Wang, Yifan; Du, Jingyu; Zou, Beiji; Chen, Yan

2018-03-01

Authentication and copyright identification are two critical security issues for medical images. Although zerowatermarking schemes can provide durable, reliable and distortion-free protection for medical images, the existing zerowatermarking schemes for medical images still face two problems. On one hand, they rarely considered the distinguishability for medical images, which is critical because different medical images are sometimes similar to each other. On the other hand, their robustness against geometric attacks, such as cropping, rotation and flipping, is insufficient. In this study, a novel discriminative and robust zero-watermarking (DRZW) is proposed to address these two problems. In DRZW, content-based features of medical images are first extracted based on completed local binary pattern (CLBP) operator to ensure the distinguishability and robustness, especially against geometric attacks. Then, master shares and ownership shares are generated from the content-based features and watermark according to (2,2) visual cryptography. Finally, the ownership shares are stored for authentication and copyright identification. For queried medical images, their content-based features are extracted and master shares are generated. Their watermarks for authentication and copyright identification are recovered by stacking the generated master shares and stored ownership shares. 200 different medical images of 5 types are collected as the testing data and our experimental results demonstrate that DRZW ensures both the accuracy and reliability of authentication and copyright identification. When fixing the false positive rate to 1.00%, the average value of false negative rates by using DRZW is only 1.75% under 20 common attacks with different parameters.

Identification of an interstellar oxide grain from the Murchison meteorite by ion imaging

NASA Technical Reports Server (NTRS)

Nittler, L. R.; Walker, R. M.; Zinner, E.; Hoppe, P.; Lewis, R. S.

1993-01-01

We report here the first use of a new ion-imaging system to locate a rare interstellar aluminum oxide grain in a Murchison acid residue. While several types of carbon-rich interstellar grains, including graphite, diamond, SiC, and TiC, have previously been found, isotopically anomalous interstellar oxide grains have proven more elusive. We have developed an ion imaging system which allows us to map the isotopic composition of large numbers of grains relatively quickly and is, thus, ideally suited to search for isotopically exotic subsets of grains. The system consists of a PHOTOMETRICS CCD camera coupled to the microchannel plate/fluorescent screen of the WU modified CAMECA IMS-3F ion microprobe. Isotopic images of the sample surface are focused on the CCD and digitized. Subsequent image processing identifies individual grains in the images and determines isotopic ratios for each. For the present work, we have imaged in O-16 and O-18; negligible contributions of (17)OH(-) and (16)OH2(-) signals to the O-18 signal allow the use of low mass resolution, simplifying the measurements. Repeated imaging runs on terrestrial corundum particles showed that the system measures isotopic ratios reproducibly to about +/- 40%. Each imaging run took about six minutes to complete, and for this study there were on average 5-15 grains in each image. We have conducted imaging searches in 2-4 micron size separates of both Orgueil and Murchison.

3D topography measurements on correlation cells—a new approach to forensic ballistics identifications

NASA Astrophysics Data System (ADS)

Song, John; Chu, Wei; Tong, Mingsi; Soons, Johannes

2014-06-01

Based on three-dimensional (3D) topography measurements on correlation cells, the National Institute of Standards and Technology (NIST) has developed the ‘NIST Ballistics Identification System (NBIS)’ aimed at accurate ballistics identifications and fast ballistics evidence searches. The 3D topographies are divided into arrays of correlation cells to identify ‘valid correlation areas’ and eliminate ‘invalid correlation areas’ from the matching and identification procedure. A ‘congruent matching cells’ (CMC)’ method using three types of identification parameters of the paired correlation cells (cross correlation function maximum CCFmax, spatial registration position in x-y and registration angle θ) is used for high accuracy ballistics identifications. ‘Synchronous processing’ is proposed for correlating multiple cell pairs at the same time to increase the correlation speed. The proposed NBIS can be used for correlations of both geometrical topographies and optical intensity images. All the correlation parameters and algorithms are in the public domain and subject to open tests. An error rate reporting procedure has been developed that can greatly add to the scientific support for the firearm and toolmark identification specialty, and give confidence to the trier of fact in court proceedings. The NBIS is engineered to employ transparent identification parameters and criteria, statistical models and correlation algorithms. In this way, interoperability between different ballistics identification systems can be more easily achieved. This interoperability will make the NBIS suitable for ballistics identifications and evidence searches with large national databases, such as the National Integrated Ballistic Information Network in the United States.

Radiology and Enterprise Medical Imaging Extensions (REMIX).

PubMed

Erdal, Barbaros S; Prevedello, Luciano M; Qian, Songyue; Demirer, Mutlu; Little, Kevin; Ryu, John; O'Donnell, Thomas; White, Richard D

2018-02-01

Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

A Novel Color Fluorescence Navigation System for Intraoperative Transcutaneous Lymphatic Mapping and Resection of Sentinel Lymph Nodes in Breast Cancer: Comparison with the Combination of Gamma Probe Scanning and Visible Dye Methods.

PubMed

Hokimoto, Norihiro; Sugimoto, Takeki; Namikawa, Tsutomu; Funakoshi, Taku; Oki, Toyokazu; Ogawa, Maho; Fukuhara, Hideo; Inoue, Keiji; Sato, Takayuki; Hanazaki, Kazuhiro

2018-01-01

This study evaluated the clinical efficacy of a novel imaging system (HyperEye Medical System [HEMS]; Mizuho Corp., Tokyo, Japan) that uses the near-infrared (NIR) fluorescence of indocyanine green to analyze sentinel lymph node (SLN) biopsies for the staging of breast cancer. This study enrolled 91 patients with histologically confirmed breast cancer that was clinically node negative with a tumor size <3 cm. We compared SLN identification rates between HEMS and conventional methods (gamma probe scanning using a colloidal radioisotope [RI] and a blue dye method) by analyzing the relationships of lymphatic to axillary lesions and SLNs. The identification rate of SLNs was 100% using HEMS, 97.8% using the RI method, and 95.6% using the blue dye method. Two types of lymphatic pathway (LP) were detected in 39 patients (42.9%) and also clearly identified using HEMS-captured color and NIR fluorescence. The incidence of two or more SLNs was significantly higher in patients with a two-route LP to the axilla group than in those with only one route (p < 0.001; 43.6 vs. 9.6%). The HEMS NIR fluorescence color imaging method is a promising potential modality for higher-level identification of SLNs than a standard combination of the RI and blue dye methods. © 2017 S. Karger AG, Basel.

Accuracy and consistency of grass pollen identification by human analysts using electron micrographs of surface ornamentation1

PubMed Central

Mander, Luke; Baker, Sarah J.; Belcher, Claire M.; Haselhorst, Derek S.; Rodriguez, Jacklyn; Thorn, Jessica L.; Tiwari, Shivangi; Urrego, Dunia H.; Wesseln, Cassandra J.; Punyasena, Surangi W.

2014-01-01

• Premise of the study: Humans frequently identify pollen grains at a taxonomic rank above species. Grass pollen is a classic case of this situation, which has led to the development of computational methods for identifying grass pollen species. This paper aims to provide context for these computational methods by quantifying the accuracy and consistency of human identification. • Methods: We measured the ability of nine human analysts to identify 12 species of grass pollen using scanning electron microscopy images. These are the same images that were used in computational identifications. We have measured the coverage, accuracy, and consistency of each analyst, and investigated their ability to recognize duplicate images. • Results: Coverage ranged from 87.5% to 100%. Mean identification accuracy ranged from 46.67% to 87.5%. The identification consistency of each analyst ranged from 32.5% to 87.5%, and each of the nine analysts produced considerably different identification schemes. The proportion of duplicate image pairs that were missed ranged from 6.25% to 58.33%. • Discussion: The identification errors made by each analyst, which result in a decline in accuracy and consistency, are likely related to psychological factors such as the limited capacity of human memory, fatigue and boredom, recency effects, and positivity bias. PMID:25202649

The Design and Development of Test Platform for Wheat Precision Seeding Based on Image Processing Techniques

NASA Astrophysics Data System (ADS)

Li, Qing; Lin, Haibo; Xiu, Yu-Feng; Wang, Ruixue; Yi, Chuijie

The test platform of wheat precision seeding based on image processing techniques is designed to develop the wheat precision seed metering device with high efficiency and precision. Using image processing techniques, this platform gathers images of seeds (wheat) on the conveyer belt which are falling from seed metering device. Then these data are processed and analyzed to calculate the qualified rate, reseeding rate and leakage sowing rate, etc. This paper introduces the whole structure, design parameters of the platform and hardware & software of the image acquisition system were introduced, as well as the method of seed identification and seed-space measurement using image's threshold and counting the seed's center. By analyzing the experimental result, the measurement error is less than ± 1mm.

3D ocular ultrasound using gaze tracking on the contralateral eye: a feasibility study.

PubMed

Afsham, Narges; Najafi, Mohammad; Abolmaesumi, Purang; Rohling, Robert

2011-01-01

A gaze-deviated examination of the eye with a 2D ultrasound transducer is a common and informative ophthalmic test; however, the complex task of the pose estimation of the ultrasound images relative to the eye affects 3D interpretation. To tackle this challenge, a novel system for 3D image reconstruction based on gaze tracking of the contralateral eye has been proposed. The gaze fixates on several target points and, for each fixation, the pose of the examined eye is inferred from the gaze tracking. A single camera system has been developed for pose estimation combined with subject-specific parameter identification. The ultrasound images are then transformed to the coordinate system of the examined eye to create a 3D volume. Accuracy of the proposed gaze tracking system and the pose estimation of the eye have been validated in a set of experiments. Overall system error, including pose estimation and calibration, are 3.12 mm and 4.68 degrees.

Postmortem computed tomography (PMCT) and disaster victim identification.

PubMed

Brough, A L; Morgan, B; Rutty, G N

2015-09-01

Radiography has been used for identification since 1927, and established a role in mass fatality investigations in 1949. More recently, postmortem computed tomography (PMCT) has been used for disaster victim identification (DVI). PMCT offers several advantages compared with fluoroscopy, plain film and dental X-rays, including: speed, reducing the number of on-site personnel and imaging modalities required, making it potentially more efficient. However, there are limitations that inhibit the international adoption of PMCT into routine practice. One particular problem is that due to the fact that forensic radiology is a relatively new sub-speciality, there are no internationally established standards for image acquisition, image interpretation and archiving. This is reflected by the current INTERPOL DVI form, which does not contain a PMCT section. The DVI working group of the International Society of Forensic Radiology and Imaging supports the use of imaging in mass fatality response and has published positional statements in this area. This review will discuss forensic radiology, PMCT, and its role in disaster victim identification.

A RONI Based Visible Watermarking Approach for Medical Image Authentication.

PubMed

Thanki, Rohit; Borra, Surekha; Dwivedi, Vedvyas; Borisagar, Komal

2017-08-09

Nowadays medical data in terms of image files are often exchanged between different hospitals for use in telemedicine and diagnosis. Visible watermarking being extensively used for Intellectual Property identification of such medical images, leads to serious issues if failed to identify proper regions for watermark insertion. In this paper, the Region of Non-Interest (RONI) based visible watermarking for medical image authentication is proposed. In this technique, to RONI of the cover medical image is first identified using Human Visual System (HVS) model. Later, watermark logo is visibly inserted into RONI of the cover medical image to get watermarked medical image. Finally, the watermarked medical image is compared with the original medical image for measurement of imperceptibility and authenticity of proposed scheme. The experimental results showed that this proposed scheme reduces the computational complexity and improves the PSNR when compared to many existing schemes.

Optimality of the basic colour categories for classification

PubMed Central

Griffin, Lewis D

2005-01-01

Categorization of colour has been widely studied as a window into human language and cognition, and quite separately has been used pragmatically in image-database retrieval systems. This suggests the hypothesis that the best category system for pragmatic purposes coincides with human categories (i.e. the basic colours). We have tested this hypothesis by assessing the performance of different category systems in a machine-vision task. The task was the identification of the odd-one-out from triples of images obtained using a web-based image-search service. In each triple, two of the images had been retrieved using the same search term, the other a different term. The terms were simple concrete nouns. The results were as follows: (i) the odd-one-out task can be performed better than chance using colour alone; (ii) basic colour categorization performs better than random systems of categories; (iii) a category system that performs better than the basic colours could not be found; and (iv) it is not just the general layout of the basic colours that is important, but also the detail. We conclude that (i) the results support the plausibility of an explanation for the basic colours as a result of a pressure-to-optimality and (ii) the basic colours are good categories for machine vision image-retrieval systems. PMID:16849219

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

NASA Astrophysics Data System (ADS)

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.

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

Rey, P.; Gourinard, Y.; Cambou, F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Significant results of the ARNICA program from August 1972 - January 1973 have been: (1) establishment of image to object correspondence codes for all types of soil use and forestry in northern Spain; (2) establishment of a transfer procedure between qualitative (remote identification and remote interpretation) and quantitative (numerization, storage, automatic statistical cartography) use of images; (3) organization of microdensitometric data processing and automatic cartography software; and (4) development of a system for measuring reflectance simultaneous with imagery.

Structural Acoustic UXO Detection and Identification in Marine Environments - Interim Report for SERDP MR-2103 Follow-On

DTIC Science & Technology

2015-07-30

into the image processing algorithm the AUV position data available from the Doppler Velocity Log (DVL) and Inertial Measurement Unit ( IMU ) systems...uncertainty due to unknown sensor z coordinates. We considered both AUV altitude and roll but not pitch which we assumed to have a small effect on the...buried target. Taken together, the images suggest that the block is buried horizontally but rolled along its long axis ~80° such that the exposed large

Intraluminal laser atherectomy with ultrasound and electromagnetic guidance

NASA Astrophysics Data System (ADS)

Gregory, Kenton W.; Aretz, H. Thomas; Martinelli, Michael A.; LeDet, Earl G.; Hatch, G. F.; Gregg, Richard E.; Sedlacek, Tomas; Haase, Wayne C.

1991-05-01

The MagellanTM coronary laser atherectomy system is described. It uses high- resolution ultrasound imaging and electromagnetic sensing to provide real-time guidance and control of laser therapy in the coronary arteries. The system consists of a flexible catheter, an electromagnetic navigation antenna, a sensor signal processor and a computer for image processing and display. The small, flexible catheter combines an ultrasound transducer and laser delivery optics, aimed at the artery wall, and an electromagnetic receiving sensor. An extra-corporeal electromagnetic transmit antenna, in combination with catheter sensors, locates the position of the ultrasound and laser beams in the artery. Navigation and ultrasound data are processed electronically to produce real-time, transverse, and axial cross-section images of the artery wall at selected locations. By exploiting the ability of ultrasound to image beneath the surface of artery walls, it is possible to identify candidate treatment sites and perform safe radial laser debulking of atherosclerotic plaque with reduced danger of perforation. The utility of the system in plaque identification and ablation is demonstrated with imaging and experimental results.

QR-on-a-chip: a computer-recognizable micro-pattern engraved microfluidic device for high-throughput image acquisition.

PubMed

Yun, Kyungwon; Lee, Hyunjae; Bang, Hyunwoo; Jeon, Noo Li

2016-02-21

This study proposes a novel way to achieve high-throughput image acquisition based on a computer-recognizable micro-pattern implemented on a microfluidic device. We integrated the QR code, a two-dimensional barcode system, onto the microfluidic device to simplify imaging of multiple ROIs (regions of interest). A standard QR code pattern was modified to arrays of cylindrical structures of polydimethylsiloxane (PDMS). Utilizing the recognition of the micro-pattern, the proposed system enables: (1) device identification, which allows referencing additional information of the device, such as device imaging sequences or the ROIs and (2) composing a coordinate system for an arbitrarily located microfluidic device with respect to the stage. Based on these functionalities, the proposed method performs one-step high-throughput imaging for data acquisition in microfluidic devices without further manual exploration and locating of the desired ROIs. In our experience, the proposed method significantly reduced the time for the preparation of an acquisition. We expect that the method will innovatively improve the prototype device data acquisition and analysis.

Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning.

PubMed

DeChant, Chad; Wiesner-Hanks, Tyr; Chen, Siyuan; Stewart, Ethan L; Yosinski, Jason; Gore, Michael A; Nelson, Rebecca J; Lipson, Hod

2017-11-01

Northern leaf blight (NLB) can cause severe yield loss in maize; however, scouting large areas to accurately diagnose the disease is time consuming and difficult. We demonstrate a system capable of automatically identifying NLB lesions in field-acquired images of maize plants with high reliability. This approach uses a computational pipeline of convolutional neural networks (CNNs) that addresses the challenges of limited data and the myriad irregularities that appear in images of field-grown plants. Several CNNs were trained to classify small regions of images as containing NLB lesions or not; their predictions were combined into separate heat maps, then fed into a final CNN trained to classify the entire image as containing diseased plants or not. The system achieved 96.7% accuracy on test set images not used in training. We suggest that such systems mounted on aerial- or ground-based vehicles can help in automated high-throughput plant phenotyping, precision breeding for disease resistance, and reduced pesticide use through targeted application across a variety of plant and disease categories.

Performance of an image analysis processing system for hen tracking in an environmental preference chamber.

PubMed

Kashiha, Mohammad Amin; Green, Angela R; Sales, Tatiana Glogerley; Bahr, Claudia; Berckmans, Daniel; Gates, Richard S

2014-10-01

Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared with the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed. ©2014 Poultry Science Association Inc.

Iris Recognition: The Consequences of Image Compression

NASA Astrophysics Data System (ADS)

Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig

2010-12-01

Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

New chemical probe technologies: applications to imaging and drug discovery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bogyo, Matthew

2017-02-01

Proteases are enzymes that play pathogenic roles in many common human diseases such as cancer, asthma, arthritis, atherosclerosis and infection by pathogens. Tools to dynamically monitor their activity can be used as diagnostic agents, as imaging contrast agents for intra-operative image guidance and for the identification of novel classes of protease-targeted drugs. I will describe our efforts to design and synthesize small molecule probes that produce a fluorescent signal upon binding to a protease target. We have identified probes that show tumor-specific retention, fast activation kinetics, and rapid systemic distribution making them useful for real-time fluorescence guided tumor resection and other diagnostic imaging applications.

Ship Detection Using High Resolution Satellite Imagery and Space-Based AIS

NASA Astrophysics Data System (ADS)

Hannevik, Tonje Nanette; Skauen, Andreas N.; Olsen, R. B.

2013-03-01

This paper presents a trial carried out in the Malangen area close to Tromsø city in the north of Norway in September 2010. High resolution Synthetic Aperture Radar (SAR) images from RADARSAT-2 were used to analyse how SAR images and cooperative reporting can be combined. Data from the Automatic Identification System, both land-based and space-based, have been used to identify detected vessels in the SAR images. The paper presents results of ship detection in high resolution RADARSAT-2 Standard Quad-Pol images, and how these results together with land-based and space-based AIS can be used. Some examples of tracking of vessels are also shown.

Identifying explosives using broadband millimeter-wave imaging

NASA Astrophysics Data System (ADS)

Weatherall, James C.; Yam, Kevin; Barber, Jeffrey; Smith, Barry T.; Smith, Peter R.; Greca, Joseph

2017-05-01

Millimeter wave imaging is employed in Advanced Technology Imaging (AIT) systems to screen personnel for concealed explosives and weapons. AIT systems deployed in airports auto-detect potential threats by highlighting their location on a generic outline of a person using imaging data collected over a range of frequency. We show how the spectral information from the imaging data can be used to identify the composition of an anomalous object, in particular if it is an explosive material. The discriminative value of the technique was illustrated on military sheet explosive using millimeter-wave reflection data at frequencies 18 - 40 GHz, and commercial explosives using 2 - 18 GHz, but the free-space measurement was limited to a single horn with a large-area sample. This work extends the method to imaging data collected at high resolution with a 18 - 40 GHz imaging system. The identification of explosives is accomplished by extracting the dielectric constant from the free-space, multifrequency data. The reflection coefficient is a function of frequency because of propagation effects associated with the material's complex dielectric constant, which include interference from multiple reflections and energy loss in the sample. The dielectric constant is obtained by numerically fitting the reflection coefficient as a function of frequency to an optical model. In principal, the implementation of this technique in standoff imaging systems would allow threat assessment to be accomplished within the scope of millimeter-wave screening.

Monitoring and guidance of HIFU beams with dual-mode ultrasound arrays.

PubMed

Ballard, John R; Casper, Andrew J; Ebbini, Emad S

2009-01-01

We present experimental results illustrating the unique advantages of dual-mode array (DMUA) systems in monitoring and guidance of high intensity focused ultrasound (HIFU) lesion formation. DMUAs offer a unique paradigm in image-guided surgery; one in which images obtained using the same therapeutic transducer provide feedback for: 1) refocusing the array in the presence of strongly scattering objects, e.g. the ribs, 2) temperature change at the intended location of the HIFU focus, and 3) changes in the echogenicity of the tissue in response to therapeutic HIFU. These forms of feedback have been demonstrated in vitro in preparation for the design and implementation of a real-time system for imaging and therapy with DMUAs. The results clearly demonstrate that DMUA image feedback is spatially accurate and provide sufficient spatial and contrast resolution for identification of high contrast objects like the ribs and significant blood vessels in the path of the HIFU beam.

Automated Microbiological Detection/Identification System

PubMed Central

Aldridge, C.; Jones, P. W.; Gibson, S.; Lanham, J.; Meyer, M.; Vannest, R.; Charles, R.

1977-01-01

An automated, computerized system, the AutoMicrobic System, has been developed for the detection, enumeration, and identification of bacteria and yeasts in clinical specimens. The biological basis for the system resides in lyophilized, highly selective and specific media enclosed in wells of a disposable plastic cuvette; introduction of a suitable specimen rehydrates and inoculates the media in the wells. An automated optical system monitors, and the computer interprets, changes in the media, with enumeration and identification results automatically obtained in 13 h. Sixteen different selective media were developed and tested with a variety of seeded (simulated) and clinical specimens. The AutoMicrobic System has been extensively tested with urine specimens, using a urine test kit (Identi-Pak) that contains selective media for Escherichia coli, Proteus species, Pseudomonas aeruginosa, Klebsiella-Enterobacter species, Serratia species, Citrobacter freundii, group D enterococci, Staphylococcus aureus, and yeasts (Candida species and Torulopsis glabrata). The system has been tested with 3,370 seeded urine specimens and 1,486 clinical urines. Agreement with simultaneous conventional (manual) cultures, at levels of 70,000 colony-forming units per ml (or more), was 92% or better for seeded specimens; clinical specimens yielded results of 93% or better for all organisms except P. aeruginosa, where agreement was 86%. System expansion in progress includes antibiotic susceptibility testing and compatibility with most types of clinical specimens. Images PMID:334798

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

A novel snapshot polarimetric imager

NASA Astrophysics Data System (ADS)

Wong, Gerald; McMaster, Ciaran; Struthers, Robert; Gorman, Alistair; Sinclair, Peter; Lamb, Robert; Harvey, Andrew R.

2012-10-01

Polarimetric imaging (PI) is of increasing importance in determining additional scene information beyond that of conventional images. For very long-range surveillance, image quality is degraded due to turbulence. Furthermore, the high magnification required to create images with sufficient spatial resolution suitable for object recognition and identification require long focal length optical systems. These are incompatible with the size and weight restrictions for aircraft. Techniques which allow detection and recognition of an object at the single pixel level are therefore likely to provide advance warning of approaching threats or long-range object cueing. PI is a technique that has the potential to detect object signatures at the pixel level. Early attempts to develop PI used rotating polarisers (and spectral filters) which recorded sequential polarized images from which the complete Stokes matrix could be derived. This approach has built-in latency between frames and requires accurate registration of consecutive frames to analyze real-time video of moving objects. Alternatively, multiple optical systems and cameras have been demonstrated to remove latency, but this approach increases cost and bulk of the imaging system. In our investigation we present a simplified imaging system that divides an image into two orthogonal polarimetric components which are then simultaneously projected onto a single detector array. Thus polarimetric data is recorded without latency on a single snapshot. We further show that, for pixel-level objects, the data derived from only two orthogonal states (H and V) is sufficient to increase the probability of detection whilst reducing false alarms compared to conventional unpolarised imaging.

Systems of Geo Positioning of the Mobile Robot

NASA Astrophysics Data System (ADS)

Momot, M. V.; Proskokov, A. V.; Nesteruk, D. N.; Ganiyev, M.; Biktimirov, A. S.

2017-07-01

Article is devoted to the analysis of opportunities of electronic instruments, such as a gyroscope, the accelerometer, the magnetometer together, the video system of image identification and system of infrared indicators during creation of system of exact positioning of the mobile robot. Results of testing and the operating algorithms are given. Possibilities of sharing of these devices and their association in a single system are analyzed. Conclusions on development of opportunities and elimination of shortcomings of the received end-to-end system of positioning of the robot are drawn.

Study on user interface of pathology picture archiving and communication system.

PubMed

Kim, Dasueran; Kang, Peter; Yun, Jungmin; Park, Sung-Hye; Seo, Jeong-Wook; Park, Peom

2014-01-01

It is necessary to improve the pathology workflow. A workflow task analysis was performed using a pathology picture archiving and communication system (pathology PACS) in order to propose a user interface for the Pathology PACS considering user experience. An interface analysis of the Pathology PACS in Seoul National University Hospital and a task analysis of the pathology workflow were performed by observing recorded video. Based on obtained results, a user interface for the Pathology PACS was proposed. Hierarchical task analysis of Pathology PACS was classified into 17 tasks including 1) pre-operation, 2) text, 3) images, 4) medical record viewer, 5) screen transition, 6) pathology identification number input, 7) admission date input, 8) diagnosis doctor, 9) diagnosis code, 10) diagnosis, 11) pathology identification number check box, 12) presence or absence of images, 13) search, 14) clear, 15) Excel save, 16) search results, and 17) re-search. And frequently used menu items were identified and schematized. A user interface for the Pathology PACS considering user experience could be proposed as a preliminary step, and this study may contribute to the development of medical information systems based on user experience and usability.

Hyperspectral imaging for melanoma screening

NASA Astrophysics Data System (ADS)

Martin, Justin; Krueger, James; Gareau, Daniel

2014-03-01

The 5-year survival rate for patients diagnosed with Melanoma, a deadly form of skin cancer, in its latest stages is about 15%, compared to over 90% for early detection and treatment. We present an imaging system and algorithm that can be used to automatically generate a melanoma risk score to aid clinicians in the early identification of this form of skin cancer. Our system images the patient's skin at a series of different wavelengths and then analyzes several key dermoscopic features to generate this risk score. We have found that shorter wavelengths of light are sensitive to information in the superficial areas of the skin while longer wavelengths can be used to gather information at greater depths. This accompanying diagnostic computer algorithm has demonstrated much higher sensitivity and specificity than the currently commercialized system in preliminary trials and has the potential to improve the early detection of melanoma.

Processing system of jaws tomograms for pathology identification and surgical guide modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Putrik, M. B., E-mail: pmb-88@mail.ru; Ivanov, V. Yu.; Lavrentyeva, Yu. E.

The aim of the study is to create an image processing system, which allows dentists to find pathological resorption and to build surgical guide surface automatically. X-rays images of jaws from cone beam tomography or spiral computed tomography are the initial data for processing. One patient’s examination always includes up to 600 images (or tomograms), that’s why the development of processing system for fast automation search of pathologies is necessary. X-rays images can be useful not for only illness diagnostic but for treatment planning too. We have studied the case of dental implantation – for successful surgical manipulations surgical guidesmore » are used. We have created a processing system that automatically builds jaw and teeth boundaries on the x-ray image. After this step, obtained teeth boundaries used for surgical guide surface modeling and jaw boundaries limit the area for further pathologies search. Criterion for the presence of pathological resorption zones inside the limited area is based on statistical investigation. After described actions, it is possible to manufacture surgical guide using 3D printer and apply it in surgical operation.« less

Automatic detection system of shaft part surface defect based on machine vision

NASA Astrophysics Data System (ADS)

Jiang, Lixing; Sun, Kuoyuan; Zhao, Fulai; Hao, Xiangyang

2015-05-01

Surface physical damage detection is an important part of the shaft parts quality inspection and the traditional detecting methods are mostly human eye identification which has many disadvantages such as low efficiency, bad reliability. In order to improve the automation level of the quality detection of shaft parts and establish its relevant industry quality standard, a machine vision inspection system connected with MCU was designed to realize the surface detection of shaft parts. The system adopt the monochrome line-scan digital camera and use the dark-field and forward illumination technology to acquire images with high contrast; the images were segmented to Bi-value images through maximum between-cluster variance method after image filtering and image enhancing algorithms; then the mainly contours were extracted based on the evaluation criterion of the aspect ratio and the area; then calculate the coordinates of the centre of gravity of defects area, namely locating point coordinates; At last, location of the defects area were marked by the coding pen communicated with MCU. Experiment show that no defect was omitted and false alarm error rate was lower than 5%, which showed that the designed system met the demand of shaft part on-line real-time detection.

Fluorescent Molecular Rotor-in-Paraffin Waxes for Thermometry and Biometric Identification.

PubMed

Jin, Young-Jae; Dogra, Rubal; Cheong, In Woo; Kwak, Giseop

2015-07-08

Novel thermoresponsive sensor systems consisting of a molecular rotor (MR) and paraffin wax (PW) were developed for various thermometric and biometric identification applications. Polydiphenylacetylenes (PDPAs) coupled with long alkyl chains were used as MRs, and PWs of hydrocarbons having 16-20 carbons were utilized as phase-change materials. The PDPAs were successfully dissolved in the molten PWs and did not act as an impurity that prevents phase transition of the PWs. These PDPA-in-PW hybrids had almost the same enthalpies and phase-transition temperatures as the corresponding pure PWs. The hybrids exhibited highly reversible fluorescence (FL) changes at the critical temperatures during phase transition of the PWs. These hybrids were impregnated into common filter paper in the molten state by absorption or were encapsulated into urea resin to enhance their mechanical integrity and cyclic stability during repeated use. The wax papers could be utilized in highly advanced applications including FL image writing/erasing, an array-type thermo-indicator, and fingerprint/palmprint identification. The present findings should facilitate the development of novel fluorescent sensor systems for biometric identification and are potentially applicable for biological and biomedical thermometry.

Real life identification of partially occluded weapons in video frames

NASA Astrophysics Data System (ADS)

Hempelmann, Christian F.; Arslan, Abdullah N.; Attardo, Salvatore; Blount, Grady P.; Sirakov, Nikolay M.

2016-05-01

We empirically test the capacity of an improved system to identify not just images of individual guns, but partially occluded guns and their parts appearing in a videoframe. This approach combines low-level geometrical information gleaned from the visual images and high-level semantic information stored in an ontology enriched with meronymic part-whole relations. The main improvements of the system are handling occlusion, new algorithms, and an emerging meronomy. Well-known and commonly deployed in ontologies, actual meronomies need to be engineered and populated with unique solutions. Here, this includes adjacency of weapon parts and essentiality of parts to the threat of and the diagnosticity for a weapon. In this study video sequences are processed frame by frame. The extraction method separates colors and removes the background. Then image subtraction of the next frame determines moving targets, before morphological closing is applied to the current frame in order to clean up noise and fill gaps. Next, the method calculates for each object the boundary coordinates and uses them to create a finite numerical sequence as a descriptor. Parts identification is done by cyclic sequence alignment and matching against the nodes of the weapons ontology. From the identified parts, the most-likely weapon will be determined by using the weapon ontology.

Detection and measurement of tubulitis in renal allograft rejection

NASA Astrophysics Data System (ADS)

Hiller, John B.; Chen, Qi; Jin, Jesse S.; Wang, Yung; Yong, James L. C.

1997-04-01

Tubulitis is one of the most reliable signs of acute renal allograft rejection. It occurs when mononuclear cells are localized between the lining tubular epithelial cells with or without disruption of the tubular basement membrane. It has been found that tubulitis takes place predominantly in the regions of the distal convoluted tubules and the cortical collecting system. The image processing tasks are to find the tubule boundaries and to find the relative location of the lymphocytes and epithelial cells and tubule boundaries. The requirement for accuracy applies to determining the relative locations of the lymphocytes and the tubule boundaries. This paper will show how the different sizes and grey values of the lymphocytes and epithelial cells simplify their identification and location. Difficulties in finding the tubule boundaries image processing will be illustrated. It will be shown how proximate location of epithelial cells and the tubule boundary leads to distortion in determination of the calculated boundary. However, in tubulitis the lymphocytes and the tubule boundaries are proximate.In these cases the tubule boundary is adequately resolved and the image processing is satisfactory to determining relativity in location. An adaptive non-linear anisotropic diffusion process is presented for image filtering and segmentation. Multi-layer analysis is used to extract lymphocytes and tubulitis from images. This paper will discuss grading of tissue using the Banff system. The ability to use computer to use computer processing will be argued as obviating problems of reproducability of values for this classification. This paper will also feature discussion of alternative approaches to image processing and provide an assessment of their capability for improving the identification of the tubule boundaries.

Image simulation for automatic license plate recognition

NASA Astrophysics Data System (ADS)

Bala, Raja; Zhao, Yonghui; Burry, Aaron; Kozitsky, Vladimir; Fillion, Claude; Saunders, Craig; Rodríguez-Serrano, José

2012-01-01

Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification.

PubMed

Unger, Jakob; Merhof, Dorit; Renner, Susanne

2016-11-16

Global Plants, a collaborative between JSTOR and some 300 herbaria, now contains about 2.48 million high-resolution images of plant specimens, a number that continues to grow, and collections that are digitizing their specimens at high resolution are allocating considerable recourses to the maintenance of computer hardware (e.g., servers) and to acquiring digital storage space. We here apply machine learning, specifically the training of a Support-Vector-Machine, to classify specimen images into categories, ideally at the species level, using the 26 most common tree species in Germany as a test case. We designed an analysis pipeline and classification system consisting of segmentation, normalization, feature extraction, and classification steps and evaluated the system in two test sets, one with 26 species, the other with 17, in each case using 10 images per species of plants collected between 1820 and 1995, which simulates the empirical situation that most named species are represented in herbaria and databases, such as JSTOR, by few specimens. We achieved 73.21% accuracy of species assignments in the larger test set, and 84.88% in the smaller test set. The results of this first application of a computer vision algorithm trained on images of herbarium specimens shows that despite the problem of overlapping leaves, leaf-architectural features can be used to categorize specimens to species with good accuracy. Computer vision is poised to play a significant role in future rapid identification at least for frequently collected genera or species in the European flora.

Particle detection, number estimation, and feature measurement in gene transfer studies: optical fractionator stereology integrated with digital image processing and analysis.

PubMed

King, Michael A; Scotty, Nicole; Klein, Ronald L; Meyer, Edwin M

2002-10-01

Assessing the efficacy of in vivo gene transfer often requires a quantitative determination of the number, size, shape, or histological visualization characteristics of biological objects. The optical fractionator has become a choice stereological method for estimating the number of objects, such as neurons, in a structure, such as a brain subregion. Digital image processing and analytic methods can increase detection sensitivity and quantify structural and/or spectral features located in histological specimens. We describe a hardware and software system that we have developed for conducting the optical fractionator process. A microscope equipped with a video camera and motorized stage and focus controls is interfaced with a desktop computer. The computer contains a combination live video/computer graphics adapter with a video frame grabber and controls the stage, focus, and video via a commercial imaging software package. Specialized macro programs have been constructed with this software to execute command sequences requisite to the optical fractionator method: defining regions of interest, positioning specimens in a systematic uniform random manner, and stepping through known volumes of tissue for interactive object identification (optical dissectors). The system affords the flexibility to work with count regions that exceed the microscope image field size at low magnifications and to adjust the parameters of the fractionator sampling to best match the demands of particular specimens and object types. Digital image processing can be used to facilitate object detection and identification, and objects that meet criteria for counting can be analyzed for a variety of morphometric and optical properties. Copyright 2002 Elsevier Science (USA)

Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs.

PubMed

Morishita, Junji; Watanabe, Hideyuki; Katsuragawa, Shigehiko; Oda, Nobuhiro; Sukenobu, Yoshiharu; Okazaki, Hiroko; Nakata, Hajime; Doi, Kunio

2005-01-01

The aim of the study was to survey misfiled cases in a picture archiving and communication system environment at two hospitals and to demonstrate the potential usefulness of an automated patient recognition method for posteroanterior chest radiographs based on a template-matching technique designed to prevent filing errors. We surveyed misfiled cases obtained from different modalities in one hospital for 25 months, and misfiled cases of chest radiographs in another hospital for 17 months. For investigating the usefulness of an automated patient recognition and identification method for chest radiographs, a prospective study has been completed in clinical settings at the latter hospital. The total numbers of misfiled cases for different modalities in one hospital and for chest radiographs in another hospital were 327 and 22, respectively. The misfiled cases in the two hospitals were mainly the result of human errors (eg, incorrect manual entries of patient information, incorrect usage of identification cards in which an identification card for the previous patient was used for the next patient's image acquisition). The prospective study indicated the usefulness of the computerized method for discovering misfiled cases with a high performance (ie, an 86.4% correct warning rate for different patients and 1.5% incorrect warning rate for the same patients). We confirmed the occurrence of misfiled cases in the two hospitals. The automated patient recognition and identification method for chest radiographs would be useful in preventing wrong images from being stored in the picture archiving and communication system environment.

A highly sensitive quantitative cytosensor technique for the identification of receptor ligands in tissue extracts.

PubMed

Lenkei, Z; Beaudet, A; Chartrel, N; De Mota, N; Irinopoulou, T; Braun, B; Vaudry, H; Llorens-Cortes, C

2000-11-01

Because G-protein-coupled receptors (GPCRs) constitute excellent putative therapeutic targets, functional characterization of orphan GPCRs through identification of their endogenous ligands has great potential for drug discovery. We propose here a novel single cell-based assay for identification of these ligands. This assay involves (a) fluorescent tagging of the GPCR, (b) expression of the tagged receptor in a heterologous expression system, (c) incubation of the transfected cells with fractions purified from tissue extracts, and (d) imaging of ligand-induced receptor internalization by confocal microscopy coupled to digital image quantification. We tested this approach in CHO cells stably expressing the NT1 neurotensin receptor fused to EGFP (enhanced green fluorescent protein), in which neurotensin promoted internalization of the NT1-EGFP receptor in a dose-dependent fashion (EC(50) = 0.98 nM). Similarly, four of 120 consecutive reversed-phase HPLC fractions of frog brain extracts promoted internalization of the NT1-EGFP receptor. The same four fractions selectively contained neurotensin, an endogenous ligand of the NT1 receptor, as detected by radioimmunoassay and inositol phosphate production. The present internalization assay provides a highly specific quantitative cytosensor technique with sensitivity in the nanomolar range that should prove useful for the identification of putative natural and synthetic ligands for GPCRs.

A robust firearm identification algorithm of forensic ballistics specimens

NASA Astrophysics Data System (ADS)

Chuan, Z. L.; Jemain, A. A.; Liong, C.-Y.; Ghani, N. A. M.; Tan, L. K.

2017-09-01

There are several inherent difficulties in the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%.

Assessment of Safety and Interference Issues of Radio Frequency Identification Devices in 0.3 Tesla Magnetic Resonance Imaging and Computed Tomography

PubMed Central

Periyasamy, M.; Dhanasekaran, R.

2014-01-01

The objective of this study was to evaluate two issues regarding magnetic resonance imaging (MRI) including device functionality and image artifacts for the presence of radio frequency identification devices (RFID) in association with 0.3 Tesla at 12.7 MHz MRI and computed tomography (CT) scanning. Fifteen samples of RFID tags with two different sizes (wristband and ID card types) were tested. The tags were exposed to several MR-imaging conditions during MRI examination and X-rays of CT scan. Throughout the test, the tags were oriented in three different directions (axial, coronal, and sagittal) relative to MRI system in order to cover all possible situations with respect to the patient undergoing MRI and CT scanning, wearing a RFID tag on wrist. We observed that the tags did not sustain physical damage with their functionality remaining unaffected even after MRI and CT scanning, and there was no alternation in previously stored data as well. In addition, no evidence of either signal loss or artifact was seen in the acquired MR and CT images. Therefore, we can conclude that the use of this passive RFID tag is safe for a patient undergoing MRI at 0.3 T/12.7 MHz and CT Scanning. PMID:24701187

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

Multimodality animal rotation imaging system (Mars) for in vivo detection of intraperitoneal tumors.

PubMed

Pizzonia, John; Holmberg, Jennie; Orton, Sean; Alvero, Ayesha; Viteri, Oscar; McLaughlin, William; Feke, Gil; Mor, Gil

2012-01-01

PROBLEM Ovarian cancer stem cells (OCSCs) have been postulated as the potential source of recurrence and chemoresistance. Therefore identification of OvCSC and their complete removal is a pivotal stage for the treatment of ovarian cancer. The objective of the following study was to develop a new in vivo imaging model that allows for the detection and monitoring of OCSCs. METHOD OF STUDY  OCSCs were labeled with X-Sight 761 Nanospheres and injected intra-peritoneally (i.p.) and sub-cutaneously (s.c.) to Athymic nude mice. The Carestream In-Vivo Imaging System FX was used to obtain X-ray and, concurrently, near-infrared fluorescence images. Tumor images in the mouse were observed from different angles by automatic rotation of the mouse. RESULTS  X-Sight 761 Nanospheres labeled almost 100% of the cells. No difference on growth rate was observed between labeled and unlabeled cells. Tumors were observed and monitoring revealed strong signaling up to 21 days. CONCLUSION  We describe the use of near-infrared nanoparticle probes for in vivo imaging of metastatic ovarian cancer models. Visualization of multiple sites around the animals was enhanced with the use of the Carestream Multimodal Animal Rotation System. © 2011 John Wiley & Sons A/S.

Electric organ discharges and electric images during electrolocation

NASA Technical Reports Server (NTRS)

Assad, C.; Rasnow, B.; Stoddard, P. K.

1999-01-01

Weakly electric fish use active electrolocation - the generation and detection of electric currents - to explore their surroundings. Although electrosensory systems include some of the most extensively understood circuits in the vertebrate central nervous system, relatively little is known quantitatively about how fish electrolocate objects. We believe a prerequisite to understanding electrolocation and its underlying neural substrates is to quantify and visualize the peripheral electrosensory information measured by the electroreceptors. We have therefore focused on reconstructing both the electric organ discharges (EODs) and the electric images resulting from nearby objects and the fish's exploratory behaviors. Here, we review results from a combination of techniques, including field measurements, numerical and semi-analytical simulations, and video imaging of behaviors. EOD maps are presented and interpreted for six gymnotiform species. They reveal diverse electric field patterns that have significant implications for both the electrosensory and electromotor systems. Our simulations generated predictions of the electric images from nearby objects as well as sequences of electric images during exploratory behaviors. These methods are leading to the identification of image features and computational algorithms that could reliably encode electrosensory information and may help guide electrophysiological experiments exploring the neural basis of electrolocation.

Neurosurgical confocal endomicroscopy: A review of contrast agents, confocal systems, and future imaging modalities

PubMed Central

Zehri, Aqib H.; Ramey, Wyatt; Georges, Joseph F.; Mooney, Michael A.; Martirosyan, Nikolay L.; Preul, Mark C.; Nakaji, Peter

2014-01-01

Background: The clinical application of fluorescent contrast agents (fluorescein, indocyanine green, and aminolevulinic acid) with intraoperative microscopy has led to advances in intraoperative brain tumor imaging. Their properties, mechanism of action, history of use, and safety are analyzed in this report along with a review of current laser scanning confocal endomicroscopy systems. Additional imaging modalities with potential neurosurgical utility are also analyzed. Methods: A comprehensive literature search was performed utilizing PubMed and key words: In vivo confocal microscopy, confocal endomicroscopy, fluorescence imaging, in vivo diagnostics/neoplasm, in vivo molecular imaging, and optical imaging. Articles were reviewed that discussed clinically available fluorophores in neurosurgery, confocal endomicroscopy instrumentation, confocal microscopy systems, and intraoperative cancer diagnostics. Results: Current clinically available fluorescent contrast agents have specific properties that provide microscopic delineation of tumors when imaged with laser scanning confocal endomicroscopes. Other imaging modalities such as coherent anti-Stokes Raman scattering (CARS) microscopy, confocal reflectance microscopy, fluorescent lifetime imaging (FLIM), two-photon microscopy, and second harmonic generation may also have potential in neurosurgical applications. Conclusion: In addition to guiding tumor resection, intraoperative fluorescence and microscopy have the potential to facilitate tumor identification and complement frozen section analysis during surgery by providing real-time histological assessment. Further research, including clinical trials, is necessary to test the efficacy of fluorescent contrast agents and optical imaging instrumentation in order to establish their role in neurosurgery. PMID:24872922

Study on high power ultraviolet laser oil detection system

NASA Astrophysics Data System (ADS)

Jin, Qi; Cui, Zihao; Bi, Zongjie; Zhang, Yanchao; Tian, Zhaoshuo; Fu, Shiyou

2018-03-01

Laser Induce Fluorescence (LIF) is a widely used new telemetry technology. It obtains information about oil spill and oil film thickness by analyzing the characteristics of stimulated fluorescence and has an important application in the field of rapid analysis of water composition. A set of LIF detection system for marine oil pollution is designed in this paper, which uses 355nm high-energy pulsed laser as the excitation light source. A high-sensitivity image intensifier is used in the detector. The upper machine sends a digital signal through a serial port to achieve nanoseconds range-gated width control for image intensifier. The target fluorescence spectrum image is displayed on the image intensifier by adjusting the delay time and the width of the pulse signal. The spectral image is coupled to CCD by lens imaging to achieve spectral display and data analysis function by computer. The system is used to detect the surface of the floating oil film in the distance of 25m to obtain the fluorescence spectra of different oil products respectively. The fluorescence spectra of oil products are obvious. The experimental results show that the system can realize high-precision long-range fluorescence detection and reflect the fluorescence characteristics of the target accurately, with broad application prospects in marine oil pollution identification and oil film thickness detection.

Linear CCD attitude measurement system based on the identification of the auxiliary array CCD

NASA Astrophysics Data System (ADS)

Hu, Yinghui; Yuan, Feng; Li, Kai; Wang, Yan

2015-10-01

Object to the high precision flying target attitude measurement issues of a large space and large field of view, comparing existing measurement methods, the idea is proposed of using two array CCD to assist in identifying the three linear CCD with multi-cooperative target attitude measurement system, and to address the existing nonlinear system errors and calibration parameters and more problems with nine linear CCD spectroscopic test system of too complicated constraints among camera position caused by excessive. The mathematical model of binocular vision and three linear CCD test system are established, co-spot composition triangle utilize three red LED position light, three points' coordinates are given in advance by Cooperate Measuring Machine, the red LED in the composition of the three sides of a triangle adds three blue LED light points as an auxiliary, so that array CCD is easier to identify three red LED light points, and linear CCD camera is installed of a red filter to filter out the blue LED light points while reducing stray light. Using array CCD to measure the spot, identifying and calculating the spatial coordinates solutions of red LED light points, while utilizing linear CCD to measure three red LED spot for solving linear CCD test system, which can be drawn from 27 solution. Measured with array CCD coordinates auxiliary linear CCD has achieved spot identification, and has solved the difficult problems of multi-objective linear CCD identification. Unique combination of linear CCD imaging features, linear CCD special cylindrical lens system is developed using telecentric optical design, the energy center of the spot position in the depth range of convergence in the direction is perpendicular to the optical axis of the small changes ensuring highprecision image quality, and the entire test system improves spatial object attitude measurement speed and precision.

Improving arrival time identification in transient elastography

NASA Astrophysics Data System (ADS)

Klein, Jens; McLaughlin, Joyce; Renzi, Daniel

2012-04-01

In this paper, we improve the first step in the arrival time algorithm used for shear wave speed recovery in transient elastography. In transient elastography, a shear wave is initiated at the boundary and the interior displacement of the propagating shear wave is imaged with an ultrasound ultra-fast imaging system. The first step in the arrival time algorithm finds the arrival times of the shear wave by cross correlating displacement time traces (the time history of the displacement at a single point) with a reference time trace located near the shear wave source. The second step finds the shear wave speed from the arrival times. In performing the first step, we observe that the wave pulse decorrelates as it travels through the medium, which leads to inaccurate estimates of the arrival times and ultimately to blurring and artifacts in the shear wave speed image. In particular, wave ‘spreading’ accounts for much of this decorrelation. Here we remove most of the decorrelation by allowing the reference wave pulse to spread during the cross correlation. This dramatically improves the images obtained from arrival time identification. We illustrate the improvement of this method on phantom and in vivo data obtained from the laboratory of Mathias Fink at ESPCI, Paris.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Yamashita, M.; Ogawa, Y.; Otani, C.; Kawase, K.

2005-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO 3 or MgO-doped LiNbO 3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a TPO, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which illegal, while one is an over-the-counter drug.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Minamide, Hiroaki; Ito, Hiromasa

2005-07-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO3 or MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave source with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni-directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a THz-wave parametric oscillator, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which are illegal, while one is an over-the-counter drug.

Preclinical Biokinetic Modelling of Tc-99m Radiophamaceuticals Obtained from Semi-Automatic Image Processing.

PubMed

Cornejo-Aragón, Luz G; Santos-Cuevas, Clara L; Ocampo-García, Blanca E; Chairez-Oria, Isaac; Diaz-Nieto, Lorenza; García-Quiroz, Janice

2017-01-01

The aim of this study was to develop a semi automatic image processing algorithm (AIPA) based on the simultaneous information provided by X-ray and radioisotopic images to determine the biokinetic models of Tc-99m radiopharmaceuticals from quantification of image radiation activity in murine models. These radioisotopic images were obtained by a CCD (charge couple device) camera coupled to an ultrathin phosphorous screen in a preclinical multimodal imaging system (Xtreme, Bruker). The AIPA consisted of different image processing methods for background, scattering and attenuation correction on the activity quantification. A set of parametric identification algorithms was used to obtain the biokinetic models that characterize the interaction between different tissues and the radiopharmaceuticals considered in the study. The set of biokinetic models corresponded to the Tc-99m biodistribution observed in different ex vivo studies. This fact confirmed the contribution of the semi-automatic image processing technique developed in this study.

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

PubMed Central

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Islam, Md. Shafiqul, E-mail: shafique@eng.ukm.my; Hannan, M.A., E-mail: hannan@eng.ukm.my; Basri, Hassan

Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensormore » intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.« less

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

NASA Astrophysics Data System (ADS)

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.

Feasibility studies on explosive detection and homeland security applications using a neutron and x-ray combined computed tomography system

NASA Astrophysics Data System (ADS)

Sinha, V.; Srivastava, A.; Lee, H. K.; Liu, X.

2013-05-01

The successful creation and operation of a neutron and X-ray combined computed tomography (NXCT) system has been demonstrated by researchers at the Missouri University of Science and Technology. The NXCT system has numerous applications in the field of material characterization and object identification in materials with a mixture of atomic numbers represented. Presently, the feasibility studies have been performed for explosive detection and homeland security applications, particularly in concealed material detection and determination of the light atomic number materials. These materials cannot be detected using traditional X-ray imaging. The new system has the capability to provide complete structural and compositional information due to the complementary nature of X-ray and neutron interactions with materials. The design of the NXCT system facilitates simultaneous and instantaneous imaging operation, promising enhanced detection capabilities of explosive materials, low atomic number materials and illicit materials for homeland security applications. In addition, a sample positioning system allowing the user to remotely and automatically manipulate the sample makes the system viable for commercial applications. Several explosives and weapon simulants have been imaged and the results are provided. The fusion algorithms which combine the data from the neutron and X-ray imaging produce superior images. This paper is a compete overview of the NXCT system for feasibility studies of explosive detection and homeland security applications. The design of the system, operation, algorithm development, and detection schemes are provided. This is the first combined neutron and X-ray computed tomography system in operation. Furthermore, the method of fusing neutron and X-ray images together is a new approach which provides high contrast images of the desired object. The system could serve as a standardized tool in nondestructive testing of many applications, especially in explosives detection and homeland security research.

Adding polarimetric imaging to depth map using improved light field camera 2.0 structure

NASA Astrophysics Data System (ADS)

Zhang, Xuanzhe; Yang, Yi; Du, Shaojun; Cao, Yu

2017-06-01

Polarization imaging plays an important role in various fields, especially for skylight navigation and target identification, whose imaging system is always required to be designed with high resolution, broad band, and single-lens structure. This paper describe such a imaging system based on light field 2.0 camera structure, which can calculate the polarization state and depth distance from reference plane for every objet point within a single shot. This structure, including a modified main lens, a multi-quadrants Polaroid, a honeycomb-liked micro lens array, and a high resolution CCD, is equal to an "eyes array", with 3 or more polarization imaging "glasses" in front of each "eye". Therefore, depth can be calculated by matching the relative offset of corresponding patch on neighboring "eyes", while polarization state by its relative intensity difference, and their resolution will be approximately equal to each other. An application on navigation under clear sky shows that this method has a high accuracy and strong robustness.

Mobile Image Based Color Correction Using Deblurring

PubMed Central

Wang, Yu; Xu, Chang; Boushey, Carol; Zhu, Fengqing; Delp, Edward J.

2016-01-01

Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. The goals of the Technology Assisted Dietary Assessment (TADA) System, developed at Purdue University, is to automatically identify and quantify foods and beverages consumed by utilizing food images acquired with a mobile device. Color correction serves as a critical step to ensure accurate food identification and volume estimation. We make use of a specifically designed color checkerboard (i.e. a fiducial marker) to calibrate the imaging system so that the variations of food appearance under different lighting conditions can be determined. In this paper, we propose an image quality enhancement technique by combining image de-blurring and color correction. The contribution consists of introducing an automatic camera shake removal method using a saliency map and improving the polynomial color correction model using the LMS color space. PMID:28572697

Application of ERTS images and image processing to regional geologic problems and geologic mapping in northern Arizona

NASA Technical Reports Server (NTRS)

Goetz, A. F. H. (Principal Investigator); Billingsley, F. C.; Gillespie, A. R.; Abrams, M. J.; Squires, R. L.; Shoemaker, E. M.; Lucchitta, I.; Elston, D. P.

1975-01-01

The author has identified the following significant results. Computer image processing was shown to be both valuable and necessary in the extraction of the proper subset of the 200 million bits of information in an ERTS image to be applied to a specific problem. Spectral reflectivity information obtained from the four MSS bands can be correlated with in situ spectral reflectance measurements after path radiance effects have been removed and a proper normalization has been made. A detailed map of the major fault systems in a 90,000 sq km area in northern Arizona was compiled from high altitude photographs and pre-existing published and unpublished map data. With the use of ERTS images, three major fault systems, the Sinyala, Bright Angel, and Mesa Butte, were identified and their full extent measured. A byproduct of the regional studies was the identification of possible sources of shallow ground water, a scarce commodity in these regions.

Verification Image of The Veins on The Back Palm with Modified Local Line Binary Pattern (MLLBP) and Histogram

NASA Astrophysics Data System (ADS)

Prijono, Agus; Darmawan Hangkawidjaja, Aan; Ratnadewi; Saleh Ahmar, Ansari

2018-01-01

The verification to person who is used today as a fingerprint, signature, personal identification number (PIN) in the bank system, identity cards, attendance, easily copied and forged. This causes the system not secure and is vulnerable to unauthorized persons to access the system. In this research will be implemented verification system using the image of the blood vessels in the back of the palms as recognition more difficult to imitate because it is located inside the human body so it is safer to use. The blood vessels located at the back of the human hand is unique, even humans twins have a different image of the blood vessels. Besides the image of the blood vessels do not depend on a person’s age, so it can be used for long term, except in the case of an accident, or disease. Because of the unique vein pattern recognition can be used in a person. In this paper, we used a modification method to perform the introduction of a person based on the image of the blood vessel that is using Modified Local Line Binary Pattern (MLLBP). The process of matching blood vessel image feature extraction using Hamming Distance. Test case of verification is done by calculating the percentage of acceptance of the same person. Rejection error occurs if a person was not matched by the system with the data itself. The 10 person with 15 image compared to 5 image vein for each person is resulted 80,67% successful Another test case of the verification is done by verified two image from different person that is forgery, and the verification will be true if the system can rejection the image forgery. The ten different person is not verified and the result is obtained 94%.

Changing Utilization of Noninvasive Diagnostic Imaging Over 2 Decades: An Examination Family-Focused Analysis of Medicare Claims Using the Neiman Imaging Types of Service Categorization System.

PubMed

Rosman, David A; Duszak, Richard; Wang, Wenyi; Hughes, Danny R; Rosenkrantz, Andrew B

2018-02-01

The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Structure of the knowledge base for an expert labeling system

NASA Technical Reports Server (NTRS)

Rajaram, N. S.

1981-01-01

One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.

Three-dimensional anisotropy contrast periodically rotated overlapping parallel lines with enhanced reconstruction (3DAC PROPELLER) on a 3.0T system: a new modality for routine clinical neuroimaging.

PubMed

Nakada, Tsutomu; Matsuzawa, Hitoshi; Fujii, Yukihiko; Takahashi, Hitoshi; Nishizawa, Masatoyo; Kwee, Ingrid L

2006-07-01

Clinical magnetic resonance imaging (MRI) has recently entered the "high-field" era, and systems equipped with 3.0-4.0T superconductive magnets are becoming the gold standard for diagnostic imaging. While higher signal-to-noise ratio (S/N) is a definite advantage of higher field systems, higher susceptibility effect remains to be a significant trade-off. To take advantage of a higher field system in performing routine clinical images of higher anatomical resolution, we implemented a vector contrast image technique to 3.0T imaging, three-dimensional anisotropy contrast (3DAC), with a PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) sequence, a method capable of effectively eliminating undesired artifacts on rapid diffusion imaging sequences. One hundred subjects (20 normal volunteers and 80 volunteers with various central nervous system diseases) participated in the study. Anisotropic diffusion-weighted PROPELLER images were obtained on a General Electric (Waukesha, WI, USA) Signa 3.0T for each axis, with b-value of 1100 sec/mm(2). Subsequently, 3DAC images were constructed using in-house software written on MATLAB (MathWorks, Natick, MA, USA). The vector contrast allows for providing exquisite anatomical detail illustrated by clear identification of all major tracts through the entire brain. 3DAC images provide better anatomical resolution for brainstem glioma than higher-resolution T2 reversed images. Degenerative processes of disease-specific tracts were clearly identified as illustrated in cases of multiple system atrophy and Joseph-Machado disease. Anatomical images of significantly higher resolution than the best current standard, T2 reversed images, were successfully obtained. As a technique readily applicable under routine clinical setting, 3DAC PROPELLER on a 3.0T system will be a powerful addition to diagnostic imaging.

Merging dietary assessment with the adolescent lifestyle.

PubMed

Schap, T E; Zhu, F; Delp, E J; Boushey, C J

2014-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children. © 2013 The Authors Journal of Human Nutrition and Dietetics © 2013 The British Dietetic Association Ltd.

Lane Marking Detection and Reconstruction with Line-Scan Imaging Data.

PubMed

Li, Lin; Luo, Wenting; Wang, Kelvin C P

2018-05-20

A bstract: Lane marking detection and localization are crucial for autonomous driving and lane-based pavement surveys. Numerous studies have been done to detect and locate lane markings with the purpose of advanced driver assistance systems, in which image data are usually captured by vision-based cameras. However, a limited number of studies have been done to identify lane markings using high-resolution laser images for road condition evaluation. In this study, the laser images are acquired with a digital highway data vehicle (DHDV). Subsequently, a novel methodology is presented for the automated lane marking identification and reconstruction, and is implemented in four phases: (1) binarization of the laser images with a new threshold method (multi-box segmentation based threshold method); (2) determination of candidate lane markings with closing operations and a marching square algorithm; (3) identification of true lane marking by eliminating false positives (FPs) using a linear support vector machine method; and (4) reconstruction of the damaged and dash lane marking segments to form a continuous lane marking based on the geometry features such as adjacent lane marking location and lane width. Finally, a case study is given to validate effects of the novel methodology. The findings indicate the new strategy is robust in image binarization and lane marking localization. This study would be beneficial in road lane-based pavement condition evaluation such as lane-based rutting measurement and crack classification.

Container weld identification using portable laser scanners

NASA Astrophysics Data System (ADS)

Taddei, Pierluigi; Boström, Gunnar; Puig, David; Kravtchenko, Victor; Sequeira, Vítor

2015-03-01

Identification and integrity verification of sealed containers for security applications can be obtained by employing noninvasive portable optical systems. We present a portable laser range imaging system capable of identifying welds, a byproduct of a container's physical sealing, with micrometer accuracy. It is based on the assumption that each weld has a unique three-dimensional (3-D) structure which cannot be copied or forged. We process the 3-D surface to generate a normalized depth map which is invariant to mechanical alignment errors and that is used to build compact signatures representing the weld. A weld is identified by performing cross correlations of its signature against a set of known signatures. The system has been tested on realistic datasets, containing hundreds of welds, yielding no false positives or false negatives and thus showing the robustness of the system and the validity of the chosen signature.

Evaluating the long-term performance of pavements thermally imaged during construction phase 1 : developing spatial tools for location identification, final report January 13, 2009.

DOT National Transportation Integrated Search

2009-01-13

This research effort was to investigate whether spatial locating equipment or Global Positioning System (GPS) equipment mounted on Connecticut Department of Transportation (ConnDOT) ARAN vans could be used to locate areas of distressed pavement. It w...