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2005 16th British Machine vision Conference, BMVC 2005

作者： Langs, Georg Peloschek, Philipp Donner, René Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Department of Diagnostic Radiology Medical University of Vienna Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria

ISBN: (纸本)1901725294

Autonomous model building is a crucial trend in model based methods like AAMs. This paper introduces an approach that deals with non-linearities by detecting distinct sub-parts in the data. Sub-models each representing an individual sub-part are derived from a minimum description length criterion. Thereby the resulting clique of models is more compact and obtains a better generalization behavior than a single model. The proposed AAM clique generation deals with non-linearities in the data in a generic information theoretic manner reducing the necessity of user interaction during training.

关键词： Information theory

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Segmentation of touching symbols for OCR of printed mathematical expressions: an approach based on multifactorial analysis

Segmentation of touching symbols for OCR of printed mathemat...

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International Conference on Document Analysis and recognition

作者： Utpal Garain B.B. Chaudhuri Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper deals with segmentation and recognition of touching characters appearing in scanned mathematical expressions. The technique is based on multifactorial analysis that integrates several factors determining cut-positions in a touching character image. A predictive algorithm is developed for efficient selection of possible cut-positions for segmenting touching characters. Experiment has been carried out using a test-set of reasonable size and results show that a considerable improvement in recognition accuracy can be achieved with a modest increase in computations.

关键词： Optical character recognition software Image segmentation Character recognition pattern recognition Image analysis Image databases pattern analysis computer vision Prediction algorithms Testing

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Neural network based word-wise handwritten script identification system for Indian postal automation

Neural network based word-wise handwritten script identifica...

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International Conference on Intelligent Sensing and Information Processing (ICISIP)

作者： K. Roy U. Pal B.B. Chaudhuri Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

Postal automation is a topic of research over the last few years. There are many works towards the postal automation in USA, UK, Japan and Australia, but for Indian postal automation there is no significant work. This paper deals with word-wise handwritten script identification for Indian postal automation. In the proposed scheme at first document skew is detected and corrected. Non-text parts are then segmented from the document using run length smoothing algorithm (RLSA). Next, using a piecewise projection method the destination address block (DAB), is at first segmented into lines and then into words. Using water reservoir concept we compute the busy-zone of the word. Finally, using matra/Shirorekha, water reservoir concept based feature, fractal based feature, etc. a neural network (NN) classifier is generated for word-wise Bangla and English scripts identification. Overall accuracy of the proposed system is at present 9 7.62%.

关键词： Neural networks Automation Natural languages Water resources Reservoirs Fractals Optical character recognition software computer vision pattern recognition USA Councils

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An approach for stemming in symbolically compressed Indian language imaged documents

An approach for stemming in symbolically compressed Indian l...

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International Conference on Document Analysis and recognition

作者： U. Garain A.K. Datta Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots, and thereby improving the overall retrieval efficiency. This paper presents an algorithm for stemming in the context of document image retrieval system. The algorithm assumes that the documents are symbolically compressed and stemming has been attempted in the compressed domain itself. Experiments have been conducted on Indian language imaged documents for which efficient OCR still remains a challenging task. Results obtained from a set 150 document images (in Bangla script, the second most popular script in the Indian sub-continent) consisting of about 12K word show a promising performance of the proposed approach.

关键词： Image coding Image retrieval Optical character recognition software Information retrieval Internet Image storage computer vision pattern recognition Search engines Character recognition

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A system for Indian postal automation

A system for Indian postal automation

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International Conference on Document Analysis and recognition

作者： K. Roy S. Vajda U. Pal B.B. Chaudhuri A. Belaid Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India LORIA Research Center Nancy France

In this paper, we present a system towards Indian postal automation based on the recognition of pin-code and city name of the postal document. In the proposed system, at first, non-text blocks (postal stamp, postal seal etc.) are detected and destination address block (DAB) is identified from the document. Next, lines and words of the DAB are segmented. Since India is a multi-lingual and multi-script country, the address part may be written by combination of two scripts. To identify the script by which a word is written, we propose a water reservoir based technique. It is very difficult to identify the script by which the pin-code portion is written. So, we have used two-stage artificial neural network (NN) based general classifiers for the recognition of pin-code digits written in English/Bangla. For recognition of city names, we propose an NSHP-HMM (non-symmetric half plane-hidden Markov model) based technique.

关键词： Automation Cities and towns pattern recognition Seals Water resources Reservoirs Neural networks Natural languages Data mining Image recognition

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A robust matching algorithm for active appearance models 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on Image Processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Beichel, Reinhard Bischof, Horst Langs, Georg Sonka, Milan Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16/2 A-8010 Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9 A-1040 Vienna Austria Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 United States

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.

关键词： Statistics

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Oriya handwritten numeral recognition system

Oriya handwritten numeral recognition system

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International Conference on Document Analysis and recognition

作者： K. Roy T. Pal U. Pal F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Engineering Mie University Tsu Mie Japan

This paper deals with recognition of off-line unconstrained Oriya handwritten numerals. To take care of variability involved in the writing style of different individuals, the features are mainly considered from the contour of the numerals. At first, the bounding box of a numeral is segmented into few blocks and chain code histogram is computed in each of the blocks. Features are mainly based on the direction chain code histogram of the contour points of these blocks. Neural network (NN) classifier and quadratic classifier are used separately for recognition and the results obtained from these two classifiers are compared. We tested the result on 3850 data collected from different individuals of various background and we obtained 90.38% (94.81%) recognition accuracy from NN (quadratic) classifier with a rejection rate of about 1.84% (1.31%), respectively.

关键词： Handwriting recognition Neural networks Shape pattern recognition Histograms computer vision Writing Testing Sorting Training data

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A novel approach to skew detection and character segmentation for handwritten bangla words

A novel approach to skew detection and character segmentatio...

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Digital Imaging Computing: Techniques and Applications, DICTA 2005

作者： Roy, A. Bhowmik, T.K. Parui, S.K. Roy, U. Dept. of Computer and System Sciences Visva-Bharati Santiniketan 731235 India IBM Global Services Pvt. Ltd. Embassy Golf Link Bangalore - 560 071 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata-700 108 India

ISBN: (纸本)0769524672

Character segmentation is a necessary preprocessing step for character recognition in many handwritten word recognition systems. The most difficult case in character segmentation is the cursive script. Fully cursive nature of Bangla handwriting, the natural skewness in words poses some challenges for automatic character segmentation. In this article a novel approach to skew detection, correction as well as character segmentation has been presented for handwritten Bangla words as a test case. Segmenting points are extracted on the basis of some patterns observed in the handwritten words. With these segmenting points a graphical path (hereafter referred to as a candidate path) has been constructed. The handwritten words contain some consistent and also inconsistent skewness. Our algorithm can cope with both types of skewness at a time. Further the method is so direct that with the help of a candidate path one can handle both skew correction and segmentation successfully, the algorithm has been tested on a database prepared for laboratory use. The method yields fairly good results for this database. © 2005 IEEE.

关键词： Image segmentation

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On foreground-background separation in low quality color document images

On foreground-background separation in low quality color doc...

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International Conference on Document Analysis and recognition

作者： Utpal Garain T. Paquet L. Heutte Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Laboratoire PSI-FRE CNRS UFR des Sciences University of Rouen Mont Saint Aignan France

This paper proposes an adaptive method for separation of foreground and background in low quality color document images. A connected component labelling is initially implemented to capture the spatially connected similar color pixels. Next, dominant background components are determined to divide the entire image into number of grids each representing local uniformity in illumination, background, etc. Finally foreground parts are located using local information around them. Several color images of old historical documents including manuscripts of high importance are used in the experiment. Apart from a qualitative evaluation, results are quantitatively compared with one popular foreground/background separation technique.

关键词： Clustering algorithms Lighting Labeling Smoothing methods Image color analysis computer vision pattern recognition Image segmentation Internet Layout

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Frequency-plane analysis of normal and pathological ECG signals for disease identification

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Journal of Medical Engineering and Technology 2005年第5期29卷 219-227页

作者： Mitra, S. Mitra, M. Chaudhuri, B.B. Department of Applied Physics Faculty of Technology University of Calcutta 92 APC Road Kolkata - 700009 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata - 700 108 India

In this paper a frequency plane analysis of both normal and diseased ECG signals is performed specifically for disease identification. Image processing techniques are used to develop an automated data acquisition package of 12 lead ECG signals from paper records. A regeneration domain is also developed to check the captured pattern with the original wave shape. A QRS complex detector with an accuracy level ∼98.4% in up to 30% signal to noise level is developed. Discrete Fourier transform (DFT) is performed to obtain the frequency spectrum of every ECG signal. Some interesting amplitude and phase response properties of chest lead V2, V3, V4, V6 and limb lead I, II, III, AVL, AVF are seen. Both amplitude and phase properties are different for normal and diseased subjects and can serve an important role in disease identification. A statistical analysis of amplitude property is carried out to show that this property is significantly different for normal and diseased subjects. © 2005 Taylor & Francis.

关键词： Electrocardiography

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