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ieee International conference on image processing

作者： Juwei Lu K.N. Plataniotis A.N. Venetsanopoulos Multimedia Laboratory Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada

Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well known that the distribution of face images, under a perceivable variation in viewpoint, illumination or facial expression, is highly nonlinear and complex. It is therefore, not surprising that linear techniques, such as those based on principle component analysis (PCA) or linear discriminant analysis (LDA) cannot provide reliable and robust solutions to those complex face recognition problems. We propose a kernel machine based discriminant analysis method, which deals with the nonlinearity of the face patterns' distribution. The proposed method also effectively solves the "small sample size" (SSS) problem which exists in most face recognition tasks. The new algorithm has been tested, in terms of error rate performance, on the multi-view UMIST Face Database. Results indicate that the proposed methodology outperform other commonly used approaches, such as the kernel-PCA (KPCA) and the generalized discriminant analysis (GDA).

关键词： Kernel Face recognition Linear discriminant analysis Lighting Principal component analysis Robustness pattern analysis Testing Error analysis Databases

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From cell image segmentation to differential diagnosis of thyroid cancer

Proceedings - International Conference on Pattern Recognitio...

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proceedings - International conference on pattern recognition 2002年第1期16卷 763-766页

作者： Ablameyko, S. Kirillov, V. Lagunovsky, D. Patsko, O. Paramonova, N. Petrou, M. Tchij, O. Institute of Engineering Cybernetics National Academy of Sciences 6 Surganov Str. 220012 Minsk Belarus Research and Clinical Institute of Radiation Medicine and Endocrinology Philimonova Str. 23 220114 Minsk Belarus University of Surrey Guildford GU2 7XH United Kingdom

An approach for cytologic diagnosis of thyroid cancer with the help of automatic morphometry is proposed. This approach is based on a developed computer analyser of images that is aimed at: automated processing.and binarization of colour images;automatic raster-to-vector transformation and formation of biological objects;morphometric assessment of biological objects by quantitative parameters characterizing the changes of cell nuclei;building of an expert system to aid the diagnosis of thyroid cancer. © 2002 ieee.

关键词： image segmentation

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Lung nodule classification utilizing support vector machines

Lung nodule classification utilizing support vector machines

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ieee International conference on image processing

作者： W.A.H. Mousa M.A.U. Khan Department of Electrical Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

Lung cancer is one of the deadly and most common diseases in the world. Radiologists fail to diagnose small pulmonary nodules in as many as 30% of positive cases. Many methods have been proposed in the literature such as neural network algorithms. Recently, support vector machines (SVMs) had received increasing attention for pattern recognition. The advantage of SVM lies in better modeling the recognition process. The objective of this paper is to apply support vector machines SVMs for classification of lung nodules. The SVM classifier is trained with features extracted from 30 nodule images and 20 non-nodule images, and is tested with features out of 16 nodule/non-nodule images. The sensitivity of SVM classifier is found to be 87.5%. We intend to automate the pre-processing.detection process to further enhance the overall classification.

关键词： Lungs Support vector machines Support vector machine classification Neural networks Artificial neural networks Minerals Feature extraction computer aided diagnosis Petroleum Cancer

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A VLSI architecture for object recognition using tree matching

A VLSI architecture for object recognition using tree matchi...

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International conference on Application Specific Systems (ASAP), Architectures and Processors

作者： K. Sitaraman N. Ranganathan A. Ejnioui Department of CSE/CMR University of South Florida Tampa FL USA School of EECS University of Central Florida Orlando FL USA

The problem of tree pattern matching for object recognition in images is computationally intensive in nature. In two-dimensional images, the objects can be represented through multiscale decomposition as tree structures. The pattern tree representing an object can be matched with a subject tree representing an image in order to detect the objects within the image. In this paper, we describe a new systolic algorithm and its realization as a VLSI chip for tree pattern matching. The hardware algorithm is based on a linear array of processing.elements (PEs) where the pattern matching is done in a pipelined fashion relying on nearest-neighbor communication between the PEs and the subject and pattern trees of arbitrary length can be processed using a fixed size PE array. The algorithm has an improved execution time of O(/spl lceil/m/a/spl rceil/n) required to perform the matching where in, a and n are the sizes of the pattern tree, processor array, subject tree respectively. A prototype CMOS VLSI chip implementing the proposed algorithm has been designed and verified It is shown that the hardware algorithm proposed in this work represent a significant improvement in terms of computational complexity, data flow, and architecture over the ones previously proposed for this problem.

关键词： Very large scale integration Object recognition pattern matching computer architecture Hardware Tree data structures Object detection Prototypes Algorithm design and analysis Computational complexity

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Combining shape from silhouette and shape from structured light for volume estimation of archaeological vessels

Proceedings - International Conference on Pattern Recognitio...

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proceedings - International conference on pattern recognition 2002年第1期16卷 364-367页

作者： Sablatnig, Robert Tosovic, Srdan Kampel, Martin Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9 183-2 A-1040 Vienna Austria

An algorithm for the automatic construction of a 3d model of archaeological vessels using two different 3d algorithms is presented. In archeology the determination of the exact volume of arbitrary vessels is of importance since this provides information about the manufacturer and the usage of the vessel. To acquire the 3d shape of objects with handles is complicated, since occlusions of the object's surface are introduced by the handle and can only be resolved by taking multiple views. Therefore, the 3d reconstruction is based on a sequence of images of the object taken from different viewpoints with two different algorithms;shape from silhouette and shape from structured light. The output of both algorithms are then used to construct a single 3d model. Results of the algorithm developed are presented for both synthetic and real input images. © 2002 ieee.

关键词： Parameter estimation

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Long term tracking using Bayesian networks

Long term tracking using Bayesian networks

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ieee International conference on image processing

作者： A.J. Abrantes J.S. Marques J.M. Lemos ISEL Instituto Superior de Engenharia de Lisboa Portugal ISR IST Instituto de Sistemas e Robótica Instituto de Engenharia de Sistemas e Computadores INESC

This paper addresses long term tracking of multiple objects with occlusions. Bayesian networks are used to model the interaction among the detected tracks and for conflict management, allowing the tracker to update the labelling decisions as soon as new information is available. If several objects overlap in the image domain and then become separated in the next frames, the proposed algorithm is able to accumulate the evidence extracted from the images and to disambiguate the competing labels. The system also provides a confidence degree for each labelling decision. Experimental results are provided to illustrate the performance of the proposed method for long term tracking of multiple pedestrians.

关键词： Bayesian methods Labeling Video sequences Hidden Markov models Data mining Object detection Detectors computer network management Video surveillance pattern recognition

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Comparison of colour spaces for optic disc localisation in retinal images

Proceedings - International Conference on Pattern Recognitio...

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proceedings - International conference on pattern recognition 2002年第1期16卷 743-746页

作者： Osareh, Alireza Mirmehdi, Majid Thomas, Barry Markham, Richard Department of Computer Science University of Bristol Bristol BS8 1UB United Kingdom Bristol Eye Hospital Bristol BS1 2LX United Kingdom

The location of the optic disc is of critical importance in retinal image analysis. In this work we improve on an approach introduced in [3] which localises an optic disc region through greylevel morphology followed by snake fitting. We propose and implement both the automatic initialisation of the snake and the application of morphology in colour space. We examine various methods of performing the morphology step (to remove the interference of blood vessels) and compare them against each other. We demonstrate that our proposed simple Lab colour morphology method is particularly suitable for the characteristics of our optic disc images. Results indicate 90.32% average accuracy in localising the optic disc boundary. © 2002 ieee.

关键词： Color image processing

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Temporal color correlograms for video retrieval

Proceedings - International Conference on Pattern Recognitio...

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proceedings - International conference on pattern recognition 2002年第1期16卷 267-270页

作者： Rautiainen, Mika Doermann, David MediaTeam Oulu Infotech Oulu University of Oulu P.O.BOx 4500 FIN-90014 Oulu Finland Laboratory for Language and Media Processing Institute for Advanced Computer Studies University of Maryland College Park MD 20742

This paper presents a novel method to retrieve segmented video shots based on their color content. The Temporal Color Correlogram captures the spatio-temporal relationship of colors in a video shot using co-occurrence statistics. The Temporal Color Correlogram extends the HSV Color Correlogram that has been found to be very effective in content-based image retrieval. Temporal Color Correlograms compute the autocorrelation of quantized HSV color values from a set of frame samples taken from a video shot. In this paper, the efficiency of the Temporal Color Correlogram and HSV Color Correlograms are evaluated against other retrieval systems participating the TREC Video track evaluation and against color histograms used commonly in content-based retrieval. We used queries and relevance judgments on the 11 hours of segmented MPEG-1 video provided to track participants. Tests are executed using our Content-Based Multimedia Retrieval System that was specifically developed for multimedia information retrieval applications. © 2002 ieee.

关键词： Color image processing

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Development of person-independent emotion recognition system based on multiple physiological signals

Development of person-independent emotion recognition system...

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： Kyung Hwan Kim Seok Won Bang Sang Ryong Kim Human-computer interaction laboratory Samsung Advanced Institute of Technology Yongin si South Korea

An emotion recognition system based on processing.of multiple physiological signals is presented. Our algorithm is developed and verified based on multiple subjects by presenting multimodal stimuli that were elaborated to effectively induce emotions, and thus not dependent on single specific user. The system utilizes physiological signals that can be acquired without discomfort from body surface. Support vector machine was introduced as pattern classifier to overcome the difficulty of large overlap among clusters and large variance within cluster. Correct classification ratio was 77.8 and 61.2%, for emotion recognition problem of three and four categories, respectively. Another advantage of our system is that it requires shorter signal monitoring time than previous ones, and thus better suited for practical use.

关键词： Emotion recognition Biomedical monitoring Signal processing Feature extraction Heart rate variability Support vector machines Signal analysis Electrocardiography Laboratories Visual databases

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Implicitization of parametric curves by matrix annihilation

Implicitization of parametric curves by matrix annihilation

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ieee International conference on image processing

作者： H. Yalcin M. Unel W. Wolovich Division of Engineering Brown University RI USA Center for Computational Vision and Control Yale University CT USA

Both parametric and implicit representations can be used to model 2D curves and 3D surfaces. Each has certain advantages compared to the other. Implicit polynomial (IP) methods are not as popular as parametric procedures because the lack of general procedures for obtaining IP models of higher degree has prevented their general use in many practical applications. In most cases today, parametric equations are used to model curves and surfaces. One such parametric representation, elliptic Fourier descriptors (EFD) has been widely used to represent 2D and 3D curves, as well as 3D surfaces. Although EFDs can represent nearly all curves, it is often convenient to have an implicit algebraic description, F(x,y)=0, especially for determining whether given points lie on the curve. Algebraic curves and surfaces have proven very useful also in many model-based applications. Various algebraic and geometric invariants obtained from these implicit models have been studied rather extensively. We present a new non-symbolic implicitization technique called the matrix annihilation method, for converting parametric Fourier representations to implicit polynomial form.

关键词： Polynomials Matrix converters Shape Equations Robust stability computer vision Solid modeling Fourier series Frequency pattern recognition

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