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Word–wise script identification from indian documents

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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An approach to a rough set decision system for classification of different heart diseases

An approach to a rough set decision system for classificatio...

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AMSE International Conference on Modelling and Simulation, MS'2004

作者： Mitra, S. Mitra, M. Chattopadhya, S. Chaudhuri, B.B. Department of Applied Physics Faculty of Technology University of Calcutta India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India JIS College of Engineering Kalyani India

In this paper a rule based rough set decision system for development of a disease inference engine is described. For this purpose an off-line data acquisition system of paper electrocardiogram (ECG) records are developed using image processing techniques. A QRS detector is developed for detection of R-R interval from ECG waves. After detection of this R-R interval the P and T waves are detected based on syntactic approaches and different time-plane features are extracted from every ECG signals. From a knowledgebase which is developed from the feedback of different reputed cardiologists and consultation of different medical books the essential time plane features for ECG interpretation have been selected. Finally, a rule-based roughest decision system is generated for the development of an inference engine for disease identification from these time-plane features.

关键词： Inference engines

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A system for word-wise handwritten script identification for Indian postal automation

A system for word-wise handwritten script identification for...

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IEEE India Conference (INDICON)

作者： K. Roy A. Banerjee U. Pal Computer Vision and Pattern Recognition Unit Indian Statistical Institute 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 piece-wise projection method the destination address block (DAB) is at first segmented into lines and then links into words. Using water reservoir concept we compute the busy-zone of the word. Finally, using matra/Shirorekha, water reservoir concept based feature, etc. a tree classifier is generated for word-wise Bangla/Devnagari and English scripts identification.

关键词： Automation Natural languages Water resources Reservoirs Optical character recognition software Australia Smoothing methods Seals Histograms Feature extraction

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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 India Conference (INDICON)

作者： Y.K. Singh S.K. Parui S. Banerjee Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

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.

关键词： Genetic algorithms Image reconstruction Image coding Filter bank PSNR Discrete wavelet transforms Signal resolution Mean square error methods Discrete transforms Mirrors

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3-D non-rigid motion estimation from image sequence based on Makov random field [Makov read Markov]

3-D non-rigid motion estimation from image sequence based on...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Ming Wang Wen-Qing Huang Kai Zheng Research Center for Computer Vision and Pattern Recognition Zhejiang University of Science and Technology Hangzhou China

ISBN: (纸本)0780384032

We propose an approach to 3-D non-rigid motion estimation from image sequence in this paper. First, with the establishment of feature point correspondence between consecutive image frames, the affine motion model and the central projection model are presented for local non-rigid motion. Then, in order to obtain the global motion parameters and overcome the ill-posed 3-D estimation problem, a framework of Markov random field (MRF) is proposed. By incorporating the motion prior constrains into the MRF, the motion smoothness feature between local regions is reflected. This converts the ill-posed problem into a well-posed one and guarantees a robust solution. Experimental results from a sequence of synthetic image sequence demonstrate the feasibility of the proposed approach.

关键词： Motion estimation Image sequences Shape Deformable models computer vision Parametric statistics Robustness pattern recognition Markov random fields Image converters

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Segmentation of coarticulated basic units in isolated Bangla words using multifactorial analysis

Segmentation of coarticulated basic units in isolated Bangla...

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IEEE India Conference (INDICON)

作者： T. Chattopadhyay B.B. Chaudhuri Systems TCS Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

One of the major challenges in speech synthesis and recognition is coarticulated unit segmentation. In this paper we present a novel technique for segmenting the basic coarticulated 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.

关键词： Speech synthesis State-space methods Databases Automatic speech recognition Image segmentation Image processing Linear predictive coding Switches Testing Signal analysis

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Identification of embedded mathematical expressions in scanned documents

Identification of embedded mathematical expressions in scann...

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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri A.R. Chaudhuri Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Department of Computer Science & Engineering Jadavpur University Kolkata India

Efficient extraction of mathematical expressions is considered as an important pre-processing step to apply existing OCR systems to convert scientific papers into their electronic format. In this correspondence, a technique for extracting embedded (or in-line) expressions has been presented. The proposed method for expression extraction initially invokes an existing OCR to recognize the input document. Several features including word n-grams (a statistical analysis of a corpus of scientific documents reveals that the word level n-gram profile for sentences containing embedded expressions is quite different from that of the sentences without any expression) are computed on sentence level to spot sentences containing expressions. Expression zones are pin pointed by exploiting OCR inability to handle expressions and by using some common typographical aspects followed in typing mathematical expressions. Experimental results on a considerable size of dataset show high efficiency of the proposed technique.

关键词： Optical character recognition software Text recognition Character recognition pattern recognition computer vision computer science Statistical analysis Embedded computing Engines Matrix converters

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A multiple-classifier system for recognition of printed mathematical symbols

A multiple-classifier system for recognition of printed math...

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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri R.P. Ghosh Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Student Department of Computer Science & Engineering MCKV Institute of Engineering Howrah West Bengal India

This paper deals with recognition of printed mathematical symbols. A group of classifiers arranged hierarchically is used to achieve robust recognition of the large number of symbols appearing in expressions. The classifier used at the top level employs stroke-based classification technique to recognize some of the frequently occurring symbols. The second level uses three classifiers to recognize the rest of the expression symbols. Different combination techniques have been attempted to integrate the second level classifiers to achieve high recognition accuracy. Experiment shows that the proposed approach is quite robust for recognition of a large number of symbols appearing in various expressions.

关键词： pattern recognition Robustness Feature extraction Shape computer vision computer science Handwriting recognition Testing Character recognition Typesetting

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Detection of QRS complex of ECG signals from square-derivative curve

Modelling, Measurement and Control C

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Modelling, Measurement and Control C 2004年第1-2期65卷 15-27页

作者： Mitra, S. Mitra, M. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata 700108 India Department of Applied Physics University College of Science and Tech. University of Calcutta Kolkata 700009 India

An approach to QRS complex detection based on the selection of maximum area zone of square derivative curve is presented in this paper. At first the ECG signals are being extracted from paper ECG records by an automated data acquisition system which has been developed by using image processing techniques. Then the QRS complex of each ECG signal is detected even in the presence of power line interference and baseline drift to calculate the sampling period for further analysis in frequency plane for disease identification. A very high accuracy level (∼ 99.4%) has been achieved in detection of QRS complex by this method.

关键词： computer vision

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Robust occupancy detection from stereo images

Robust occupancy detection from stereo images

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International Conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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