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Minutiae Triangle Graphs: A New Fingerprint Representation with Invariance Properties

Minutiae Triangle Graphs: A New Fingerprint Representation w...

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International Conference on image and vision Computing New Zealand, IVCNZ

作者： Akmal-Jahan Mohamed-Abdul-Cader Watcharapong Chaidee Jasmine Banks Vinod Chandran Vision and Signal Processing Lab School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia Signal and Image Processing Laboratory Kasetsart University Bangkok Thailand

A new algorithm for matching finger or palm prints is presented for use where the full hand is considered as a biometric and only parts may be available in images for comparison. The algorithm uses an extended version of the minutiae-based approach treating the pattern as a graph of minutiae-like points. The procedure to identify minutiae-like points uses Gabor filtering, edge detection and thinning and following line patterns. A set of such points is subjected to Delaunay triangulation yielding a starting set of base-triangles for matching. There can be multiple matches of such triangles between the template and test - as similar triangles with a tolerance in the angles. Graphs are then grown to 5 and more nodes as long as a match can be found, until the maximum size matching graph is obtained. If the test matches a significant part of the template, the maximum order of graph matched will be high. The matching process is robust to transformations such as rotation, translation and scale changes. It can be applied to any part of the hand provided minutiae-like points are identifiable prior to the matching steps. The algorithm is tested using 158 fingerprint images from FVC 2002 DB1. 100 genuine and 5048 impostor scores are generated from 46 templates and 112 testing images. It had an EER of about 6%. It proves the principle behind the methodology and demonstrates that the method can be effective with degraded fingerprint images and is robust to similarity transformations present in the data. It can be applied for forensic fingerprint matching from the palm or parts other than the fingertips. By using multiple parts and multiple templates, the accuracy of the method will be improved with fusion in future versions of the algorithm.

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Free-form object recognition and registration using surface signatures

Free-form object recognition and registration using surface ...

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IEEE International Conference on image processing

作者： S.M. Yamany A.A. Farag A. El-Bialy Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Systems and Biomedical Engineering Department Cairo University Cairo Egypt

This paper presents a new concept for 3-D free-form surface registration and object recognition using a new surface representation scheme. This representation scheme captures the 3-D curvature information of any free-form surface and encodes it into a 2-D image corresponding to a certain point on the surface. This image is unique for this point and is independent from the object translation or orientation in space. For this reason we called this image “Surface Point Signature” (SPS). This scheme can be used as a global representation of the surface as well as a local one and also in a scale independent surface matching. It performs faster registration than existing registration approaches. We applied this technique in object registration, multimodal medical image registration and the recognition of multiple objects in a 3-D scene.

关键词： Object recognition Biomedical imaging image recognition Layout Shape image processing Laboratories image registration Robot vision systems Contracts

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Multiresolution Approach for Non-Contact Measurements of Arterial Pulse using Thermal Imaging

Multiresolution Approach for Non-Contact Measurements of Art...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： S.Y. Chekmenev A.A. Farag E.A. Essock Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychological and Brain University of Louisville Louisville KY USA

This paper presents a novel, multiresolution (MR) approach for non-contact passive measurements of the arterial pulse along the arterial tree using thermal imaging of the most accessible regions of human face and neck. The method automatically detects Region/s Of Measurement (ROM) of the arterial pulse using the periodic nature of arterial thermal patterns. This ROM constitutes a skin area where the heat pulsation produced by an artery is most pronounced. The output of the algorithm is a descriptive arterial pulse waveform. To the best of our knowledge, our results are novel and have not been reported before. Some potential applications of this work are in the field of non-contact health state/ physiology monitoring, magnetic resonance imaging, smart rooms, polygraph testing, and intent identification.

关键词： Pulse measurements image resolution Read only memory Humans Face detection Neck Skin Arteries Physiology Monitoring

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Interest Point Based Tracking

Interest Point Based Tracking

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International Conference on Pattern Recognition

作者： Werner Kloihofer Martin Kampel Research and Development Image Processing Center Communication Systems GmbH Vienna Austria Computer Vision Laboratory University of Technology Vienna Vienna Austria

ISBN: (纸本)9781424475421

This paper deals with a novel method for object tracking. In the first step interest points are detected and feature descriptors around them are calculated. Sets of known points are created, allowing tracking based on point matching. The set representation is updated online at every tracking step. Our method uses one-shot learning with the first frame, so no offline and no supervised learning is required. Following an object recognition based approach there is no need for a background model or motion model, allowing tracking of abrupt motion and with non-stationary cameras. We compare our method to Mean Shift and Tracking via Online Boosting, showing the benefits of our approach.

关键词： Tracking Feature extraction computer vision Boosting Object recognition Pattern recognition Conferences

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Improving the Robustness of a Direct Visual Odometry Algorithm for Planetary Rovers

Improving the Robustness of a Direct Visual Odometry Algorit...

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International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Geovanni Martinez Image Processing and Computer Vision Research Laboratory (IPCV-LAB) School of Electrical Engineering University of Costa Rica San José Costa Rica

An algorithm capable of computing the robot position by evaluating measurements of frame to frame intensity differences was extended to be able to detect outliers in the measurements to exclude them from the evaluation to perform the positioning, with the aim of improving its robustness in irregular terrain scenes, such as consisting of flat surfaces with stones on them. The images are taken by a camera firmly attached to the robot, tilted downwards, looking at the planetary surface. A measurement is detected as an outlier only if its intensity difference and linear intensity gradients can not be described by motion compensation. According to the experimental results, this modification reduced the positioning error by a factor of one third in difficult terrain, maintaining its positioning error, which resulted in an average of 1.8%, within a range of 0.15% and 2.5% of distance traveled, similar to those achieved by state of the art algorithms successfully used in robots here on earth and on Mars.

关键词： Three-dimensional displays Cameras Visual odometry Robot vision systems Wheels Extraterrestrial measurements

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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International Conference on Information Fusion

作者： M.G. Mostafa A.A. Farag E. Essock Department of Electrical and Computer Engineering Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychology University of Louisville Louisville KY USA

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results.

关键词： image registration Neural networks Hyperspectral sensors Remote sensing image reconstruction Geometry Remote monitoring Intelligent sensors Satellites Laser radar

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Medical image registration and model construction using genetic algorithms

Medical image registration and model construction using gene...

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International Workshop on Medical Imaging and Augmented Reality, MIAR 2001

作者： Chow, Chi Kin Tsui, Hung Tat Lee, Tong Lau, Tze Kin Computer Vision and Image Processing Laboratory Chinese University of Hong Kong Shatin Hong Kong Dept. of Electron. Eng. Chinese Univ. of Hong Kong Shatin Hong Kong Dept. of Obstetrics and Gynaecology Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)0769511139

The free-form surface registration problem is important in medical image processing and reconstruction. An accurate, robust and fast solution is, therefore, of great significance. Most existing approaches, like iterative closest point (ICP) or mutual information, can only work under many assumptions or limitations. In this paper we propose an new approach using an improved genetic algorithm for finding the transformation, a translation and a rotation, between two free-form surfaces, that are partially overlapped. Application of the algorithm to 3D object model construction using multiple image integration is investigated. The experimental results showed that the improved genetic algorithm for surface registration and model constriction is robust and is faster than all existing methods in the literatures. © 2001 IEEE.

关键词： Genetic algorithms

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A new segmentation and registration approach for vertebral body analysis

A new segmentation and registration approach for vertebral b...

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IEEE International Symposium on Biomedical Imaging

作者： Melih S. Aslan Asem Ali Aly A. Farag Hossam Abdelmumin Ben Arnold Ping Xiang Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc. Columbia KY USA

To diagnose the osteoporosis accurately, the bone mineral density (BMD) measurements of the vertebral bodies (VBs) are required. In this paper, we propose a new segmentation and registration method in order to assist the BMD measurements and fracture analysis (FA) accurately. In this experiment, image appearance and shape information of VBs are used. Our shape model is required to be registered to the testing image to avoid user interaction(s). Our proposed framework has four phases: i) the detection of vertebral body (VB) using the Matched filter, ii) initial segmentation using the intensity and spatial interaction models, iii) the registration of the shape prior and initially segmented image by matching a vector distance function (VDF), and iv) final segmentation using graph cuts which integrates intensity, spatial interaction and shape prior. Preliminary results show that our new algorithm is very promising and can solve many segmentation and registration problems.

关键词： Shape image segmentation Three dimensional displays Computed tomography Bones Labeling image color analysis

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Thermographic image analysis method in detection of canine bone cancer (osteosarcoma)

Thermographic image analysis method in detection of canine b...

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Congress on image and Signal processing, CISP

作者： Maryamsadat Amini Peng Liu Scott E Umbaugh Dominic J. Marino Catherine A. Loughin Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Southern Illinois University Edwardsville IL USA Long Island Veterinary Specialists Plainview NY USA

Bone cancer is a pathologic condition which may occur for both humans and canines. This tumor develops quickly from within the bone tissue and become painful as it grows outward. A metastasized bone tumor may be cured by amputation, otherwise it will be fatal. The current diagnostic imaging methods for bone cancer are X-rays, Computed Tomography scan (CT scan), and Magnetic Resonance Imaging (MRI). The disadvantages of these methods include not enough detail in X-ray images, high dose of radiation from CT scans, and high expense of the time-consuming MRI method. In most of the bone cancer cases, when this tumor is detected by these imaging methods, it has already metastasized. The study is to investigate whether it is possible to detect canine bone cancer by thermography imaging. This alternative imaging method will decrease diagnostic time, expenses and prevent radiation exposure. The best classification success rate obtained in this study is 80.77%.

关键词： Feature extraction image color analysis Cancer Pattern classification Bones Software Histograms

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Partial shape recognition: a landmark-based approach

Partial shape recognition: a landmark-based approach

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IEEE International Conference on Systems, Man and Cybernetics

作者： N. Ansari E.J. Delp Center for Communications and Signal Processing Electrical and Computer Engineering Department New Jersey Institute of Technology Newark NJ USA Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University IN USA

A technique to guide landmark matching known as hopping dynamic programming is described. The location of the model in the scene is estimated with a least-squares fit. A heuristic measure is then computed to decide if the model is in the scene. The shape features of an object are the landmarks associated with the object. The landmarks of an object are defined as the points of interest of the object that have important shape attributes. Examples of landmarks are corners, holes, protrusions, and high-curvature points.< >

关键词： Shape measurement Layout computer vision Pattern recognition Signal processing image processing Laboratories Performance evaluation Least squares approximation Feature extraction

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