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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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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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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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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： A. Roy T.K. Bhowmik S.K. Parui U. Roy Department of Computer and System Sciences Visva Bharati University Santiniketan India Embassy Golf Link IBM Global Services Private Limited Bangalore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

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.

关键词： Image segmentation Character recognition Optical character recognition software computer vision pattern recognition Testing Databases Algorithm design and analysis Writing Handwriting recognition

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A comparative study between ISITRA and wavelet filters

A comparative study between ISITRA and wavelet filters

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IEEE INDICON 2004 - 1st India Annual Conference

作者： Singh, Yumnam Kirani Parui, Swapan Kumar Banerjee, Shuvransu Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108

ISBN: (纸本)0780389093

ISITRA is a new scheme of signal decomposition and reconstruction. In ISITRA, the space of PRF sets is much larger and more well-behaved than that in the existing schemes like filter bank or wavelets. Since such a space is constrained, it is mapped to an unconstrained space in which an optimization technique can be applied to find optimal PRF sets in terms of some criterion. Our criterion here is based on Mean Square Error and the optimization technique used is genetic algorithms. Optimal PRF sets thus found perform better than the popular Daubechies' filters for a compression task. © 2004 IEEE.

关键词： Optical filters

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A fast correlation attack for LFSR-based stream ciphers

A fast correlation attack for LFSR-based stream ciphers

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1st International Conference on Applied Cryptography and Network Security, ACNS 2003

作者： Palit, Sarbani Roy, Bimal K. De Arindom Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Applied Statistics Unit Indian Statistical Institute India Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)3540202080

This paper describes a novel fast correlation attack of stream ciphers. The salient feature of the algorithm is the absence of any pre-processing or iterative phase, an usual feature of existing fast correlation attacks. The algorithm attempts to identify a number of bits of the original linear feedback shift register (LFSR) output from the received bits of the ciphertext. These are then used to construct a system of linear equations which are subsequently solved to obtain the initial conditions. The algorithm is found to perform well for LFSRs of large sizes but having sparse polynomials. It may be noted that such polynomials have low Hamming weight which is one more than the number of feedback connections or "taps" of the corresponding LFSR. Its performance is good in situations even where limited cipherlength is available. Another important contribution of the paper is a modification of the approach when the LFSR outputs are combined by a function which is correlation immune and perhaps, unknown to the decrypter. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Polynomials

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Segmentation of co-articulated basic units in isolated Bangla words using multifactorial analysis

Segmentation of co-articulated basic units in isolated Bangl...

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IEEE INDICON 2004 - 1st India Annual Conference

作者： Chattopadhyay, Tanushyam Chaudhuri, B.B. Systems TCS Kolkata Computer Vision and Pattern Recognition Unit Indian Statistical Institute Jawaharlal Nehru

ISBN: (纸本)0780389093

One of the major challenges in speech synthesis and recognition is co-articulated unit segmentation. In this paper we present a novel technique for segmenting the basic co-articulated units using multifactorial analysis based approach. The proposed algorithm is applied on isolated spoken words in Bangla. The results obtained from a considerably large database show the strength of the approach. ©2004 IEEE.

关键词： Speech synthesis

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Word–wise script identification from indian documents

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6th IAPR International Workshop on Document Analysis Systems, DAS 2004

作者： Sinha, Suranjit Pal, Umapada Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Unit 203 B.T. Road Kolkata700 108 India

ISBN: (纸本)3540230602

In a country like India, a single text line of most of the official documents contains two different script words. Under two-language formula, the indian documents are written in English and the state official language. For Optical Character recognition (OCR) of such a document page, it is necessary to separate different script words before feeding them to the OCRs of individual scripts. In this paper a robust technique is proposed to extract word-wise script identification from indian doublet form documents. Here, at first, the document is segmented into lines and then the lines are segmented into words. Using different topological and structural features (like number of loops, headline feature, water reservoir concept based features, profile features, etc.) individual script words are identified from the documents. The proposed scheme is tested on 24210 words of different doublets and we received more than 97% accuracy, on average. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical character recognition

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