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检索条件"任意字段=2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003"

共 6678 条记录，以下是4811-4820 订阅

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Handwritten Amharic Bank Check recognition Using Hidden Markov Random Field

Handwritten Amharic Bank Check Recognition Using Hidden Mark...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Worku Alemu Siegfried Fuchs Image Processing and Recognition Group Artificial Intelligence Institute Dresden Germany

Amharic, a working language in Ethiopia, has its own writing system which is totally different from that of the Latin alphabet based languages. Amharic handwriting recognition is challenging due to the huge number of symbols, significant interclass similarity and also intra-class variability. In this paper the application of Hidden Markov Random Field (HMRF) for handwriting recognition of the legal amount field of Amharic bank check is presented. The three main contributions of this paper are the following. First, a new feature extraction technique is used which tries to extract natural features as perceived by human beings. The features extracted by this technique show a significant performance improvement. Second, a classification technique by estimating likelihood using a method known as pseudo-marginal probability is developed. The third contribution is the application of contextual information based on the syntactical structure of Amharic checks. Such context information is important in recognition process because even humans fail to recognize symbols correctly without any context. A noticeable difference is observed between results obtained with and without the application of contextual information. On the whole, despite the huge interclass similarity and also intra-class variability of handwritten Amharic characters, attractive results are found.

关键词： Pixel Feature extraction Hidden Markov models Computational modeling Handwriting recognition pattern recognition Law

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Fusion of Structure Adaptive Self-organizing Maps Using Fuzzy Integral

Fusion of Structure Adaptive Self-organizing Maps Using Fuzz...

引用

International Joint conference on Neural Networks 2003

作者： Kim, Kyung-Joong Cho, Sung-Bae Yonsei University Department of Computer Science 134 Shinchon-dong Sudaemoon-ku Seoul 120-749 Korea Republic of

Recently, many researchers attempt to develop an effective SOM-based pattern recognizer for high performance classification. Structure adaptive self-organizing map (SASOM) is a variant of SOM that is useful to pattern recognition and visualization. Fusion of classifiers can overcome the limitation of a single classifier by complementing each other. Fuzzy integral is a combination scheme that uses subjectively defined relevance of classifiers. In this paper, fusion of SASOM's using fuzzy integral is proposed for web mining problem. User profile represents different aspects of user's characteristics and needs an ensemble of classifiers that estimate user's preference using web content labeled by user as "like" or "dislike." The proposed method estimates the user profile using subsets of important features extracted from user-rated web documents. Using UCI Syskill & Webert data, the method is tested and compared with other classifiers including ID3, BP and naïve Bayes classifier. Experimental results show that the fusion of SASOM's using fuzzy integral can perform better than not only previous studies but also majority voting of SASOM's.

关键词： Self organizing maps

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Salient Features and Hypothesis Testing: evaluating a novel approach for segmentation and address block location

Salient Features and Hypothesis Testing: evaluating a novel ...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： David Menoti Dibio Leandro Borges Alceu de Souza Britto Jr Postgraduate Program in Applied Informatics (PPGIA) Pontifical Catholic University of Parana (PUCPR) Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR)

This paper presents a modification with further experiments of a segmentation algorithm based on feature selection in wavelet space of ours [9]. The aim is to automatically separate in postal envelopes the regions related to background, stamps, rubber stamps, and the address blocks. First, a typical image of a postal envelope is decomposed using Mallat algorithm and Haar basis. High frequency channel outputs are analyzed to locate salient points in order to separate the background. A statistical hypothesis test is taken to decide upon more consistent regions in order to clean out some noise left. The selected points are projected back to the original gray level image, where the evidence from the wavelet space is used to start a growing process to include the pixels more likely to belong to the regions of stamps, rubber stamps, and written area. We have modified the growing process controlled by the salient points and the results were greatly improved reaching success rate of over 97%. Experiments are run using original postal envelopes from the Brazilian Post Office Agency, and here we report results on 440 images with many different layouts and backgrounds.

关键词： Image segmentation Pixel Rubber Layout Wavelet transforms computer vision pattern recognition

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General Data Association with Possibly Unresolved Measurements Using Linear Programming

General Data Association with Possibly Unresolved Measuremen...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Huimin Chen Krishna Pattipati Thiagalingam Kirubarajan Yaakov Bar-Shalom Department of Electrical & Computer Engineering University of Connecticut Storrs CT USA Department of Electrical & Computer Engineering McMaster University Hamilton ONT Canada Department of Electrical Engineering University of New Orleans New Orleans LA USA

In this paper we formulate data association with possibly unresolved measurements as an augmented assignment problem. Unlike conventional measurement-to-track association via assignment, this augmented assignment problem has much greater complexity when each target originated measurement can be of single or multiple origins. The main point is that standard one-to-one assignment algorithms do not work in the case of unresolved measurements because the constraints in the augmented assignment problem are very different. A suboptimal approach is considered for solving the resulting optimization problem via linear programming (LP) by relaxing the integer constraints. A tracker based on probabilistic data association filter (PDAF) using the LP solutions is also discussed. Simulation results show that the percentage of track loss is significantly reduced by solving the augmented assignment rather than the conventional assignment.

关键词： Target tracking Radar tracking Time measurement Linear programming conferences Indexes Probabilistic logic

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Methods for intelligent localization and mapping during haptic exploration

Methods for intelligent localization and mapping during hapt...

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System Security and Assurance

作者： Schaeffer, Monika A. Okamura, Allison M. Department of Computer Science The Johns Hopkins University Baltimore MD 21218 United States Department of Mechanical Engineering The Johns Hopkins University Baltimore MD 21218 United States

This paper presents a set of algorithms for use in simultaneous localization and mapping during haptic exploration. Several solutions are provided for the problem of a single spherical robot finger exploring a known smooth surface, starting with an unknown pose. Using pose estimates, pattern matching is performed between the robot's internal model of the surface and the known model The robot finger is guided to explore regions of the surface that will maximize the probability of recognition. Simulation results demonstrate the effectiveness of one algorithm. In addition, it is shown that haptic exploration and dexterous manipulation can be achieved concurrently when multiple robot fingers are used.

关键词： Haptic interfaces

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Statistical Search for Hierarchical Linear Optimal Representations of Images

Statistical Search for Hierarchical Linear Optimal Represent...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Qiang Zhang Xiuwen Liu Anuj Srivastava Department of Computer Science Florida State University Tallahassee FL USA Department of Statistics Florida State University Tallahassee FL USA

Although linear representations of images are widely used in appearance-based recognition of objects, the frequently used ideas, such as PCA, ICA, and FDA, are often found to be suboptimal. A stochastic search algorithm has been proposed recently [4] for finding representations that are optimal for specific tasks and datasets. However, this search algorithm is computationally efficient only when the image size is relatively small. Here we propose a hierarchical learning algorithm to speed up the search. The proposed approach decomposes the original optimization problem into several stages according to a hierarchical organization. In particular, the following idea is applied recursively: (i) reduce the image dimension using a shrinkage matrix, (ii) optimize the recognition performance in the reduced space, and (iii)expand the optimal subspace to the bigger space in a pre-specified way. We show that the optimal performance is maintained in the last step. By applying this decomposition procedure recursively, a hierarchy of layers is formed. This speeds up the original algorithm significantly since the search is performed mainly in reduced spaces. The effectiveness of hierarchical learning is illustrated on a popular database, where the computation time is reduced by a large factor compared to the original algorithm.

关键词： Training Complexity theory Image recognition Distance measurement Pixel Algorithm design and analysis Optimization

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Direct Least Square Fitting of Paracatadioptric Line Images

Direct Least Square Fitting of Paracatadioptric Line Images

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Joao P. Barreto Helder Araujo Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

Paracatadioptric sensors combine a parabolic shaped mirror and a camera inducing an orthographic projection. Such a configuration provides a wide field of view while keeping a single effective viewpoint. In general the paracatadioptric image of a line is a conic curve. The estimation of line images is an important subject for applications such as reconstruction and visual control of motion. However the estimation of the conic curves where lines are mapped is hard to accomplish. In general only a small arc of the conic is visible in the image and conventional conic fitting techniques are unable to correctly estimate the curve. This paper shows that line images can be accurately estimated by constraining the search space. A conic curve is the paracatadioptric image of a line if, and only if, the image of the circular points lie on the curve and two certain points are conjugate with respect to the conic. Considering the space of all conic curves, the line images lie in a linear subspace which depends on the system calibration. The paracatadioptric projection of a line can estimated by fitting a conic in the subspace to the data points. The proposed approach is computationally efficient since the fitting problem can be solved by an eigensystem

关键词： Fitting Equations Cameras Noise Least squares approximation Mirrors Sensors

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computer vision Algorithms for Quantifying the Growth and Behavior of Neurons Cultured on Nanofabricated Surfaces

Computer Vision Algorithms for Quantifying the Growth and Be...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Muhammad-Amri Abdul Karim Khalid Al-Kofahi Badrinath Roysam Natalie Dowell-Mesfin Rifat J. Hussain William Shain James N. Turner Electrical Computer & Systems Engineering Dept. Rensselaer Polytechnic Institute Troy NY Electrical Computer & Systems Engineering Dept. Rensselaer Polytechnic Institute Troy NY USA The Wadsworth Center Department of Health Albany NY The Wadsworth Center Department of Health Albany NY USA

Neuron growth on nanofabricated silicon surfaces, once understood, is fundamental to engineer circuits involving neurons and electronic components, leading to applications such as next-generation brain implants, and high-throughput neurologic drug screening assay systems. Precise quantification of neuronal growth and behavior from image samples requires computer vision algorithms for automatic tracing of neurons, and flexible algorithms for reliable registration and analysis of multi-fluorophore imagery. The tracing algorithms must be robust to high levels of clutter and common imaging artifacts, process discontinuities, and quantum noise, especially when live neurons are imaged. Finally, the large numbers of images that must be processed for a hypothesis test or assay call for computationally efficient algorithms. A fully automated neuron tracing algorithm based on the use of robust detection and estimation principles is described here that meets the above needs. It takes 2 seconds to trace and extract morphological statistics from a typical 1280 × 1024 image on a Pentium III, 1 GHz personal computer. It was validated against manually generated traces and the errors were in the range of 1-5% per image.

关键词： Neurons Surface topography Algorithm design and analysis Robustness computer vision Surface morphology Nerve fibers

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Information Retrieval Based on OCR Errors in Scanned Documents

Information Retrieval Based on OCR Errors in Scanned Documen...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Y. Fataicha M. Cheriet J. Y. Nie C. Y. Suen CENPARMI Concordia University Montreal QUE Canada LIVIA Laboratory École de Technologie Supérieure QUE Canada RALI laboratory Université de Montréal QUE Canada

An important proportion of documents are document images, i.e. scanned documents. For their retrieval, it is important to recognize their contents. Current technologies for optical character recognition (OCR) and document analysis do not handle such documents adequately because of the recognition errors. In this paper, we describe an approach that integrates the detection of errors in scanned texts without relying on a lexicon, and this detection is integrated in the research process. The proposed algorithm consists of two basic steps. In the first step, we apply editing operations on OCR words that generate a collection of error-grams and correction rules. The second step uses query terms, error-grams, and correction rules to create searchable keywords, identify appropriate matching terms, and determine the degree of relevance of retrieved document images. Algorithms has been tested on 979 document images provided by Media-team databases from Washington University, and the experimental results obtained show the effectiveness of our method and indicate improvement in comparison with the standard methods such as exact or partial matching, N-gram overlaps, and Q-gram distance.

关键词： Optical character recognition software Distance measurement Text recognition Image recognition pattern recognition Character recognition Databases

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Archaeological Fragment Reconstruction Using Curve-Matching

Archaeological Fragment Reconstruction Using Curve-Matching

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Jonah C. McBride Benjamin B. Kimia Brown University Providence RI USA

We present a novel approach to the problem of puzzle solving as it relates to archaeological fragment reconstruction. We begin with a set of broken fragments. In the first stage, we compare every pair of fragments and use partial curve matching to find similar portions of their respective boundaries. Partial curve matching is typically a very difficult problem because the specification of the partial curves are highly unconstrained and curve matching is computationally expensive. To address the first problem, we only consider matches which begin at fragment corners and then use curve-matching with normalized energy to determine how far the match extends. We also reduce computational cost by employing a multi-scale approach. This allows us to quickly generate many possible matches at a coarse scale and only keep the best ones to be matched again at a finer scale. In the second stage, we take a rank-ordered list of pairwise matches to search for a globally optimal arrangement. The search is based on a best-first strategy which adds fragments with the highest pairwise affinity first, but then evaluates their confidence as part of the global solution by rewarding the formation of triple junctions which are dominant in archaeological puzzles. To prevent failure due to the inclusion of spurious matches, we employ a standard beam-search to simultaneously expand on multiple solutions. Results on several cases are demonstrated.

关键词： Junctions Length measurement computer vision Materials Complexity theory pattern recognition conferences

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