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International Conference on Document Analysis and recognition

作者： Chandranath Adak Bidyut B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Writer identification is an essential component in computational forensic. In this paper, we attempt to do this job based only on isolated characters and numerals. For that, at first, some points of interest (keypoints) on the image are detected by structural analysis and SIFT based detector. Then we calculate a set of features within a certain neighborhood of the keypoint and employ fusion rule on multiple probabilistic SVM classifiers output for writer identification. For experimental analysis, a database containing 212,300 isolated Bangla orthosyllabic characters and numerals are generated with the help of 100 writers. We obtain fairly good result to identify a writer. We also try to find a small set of highly discriminative characters storing extra information about the writing style of an individual.

关键词： Chlorine

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An MLP-based texture segmentation technique which does not require a feature set

An MLP-based texture segmentation technique which does not r...

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International Conference on pattern recognition

作者： U. Bhattacharya B.B. Chaudhuri S.K. Parui Computer Vision & Pattern Recognition Unit Indian Statistical Institute Calcutta India

In this paper we describe a texture segmentation approach without feature computation based on a multilayer perceptron network (MLP). Thus, the users need not bother about the selection and then computation of feature set and hence real-time segmentation may be possible. The basic motivation of the work is the fact that human vision does not consciously compute features for distinguishing different textures in a scene. A single hidden layer MLP network has been found to be most suitable with heuristically chosen input and hidden layer sizes. A method has been used to speedup the learning of the MLP network. The result of segmentation by a trained network usually results in misclassification in the form of speckles. For the removal of such noise an edge-preserving-noise-smoothing technique is proposed. The final segmentation accuracy is well comparable with that of other existing techniques.

关键词： computer vision Image segmentation Humans Layout pattern recognition Electronic mail computer networks Surface texture User-generated content Artificial neural networks

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Composite Script Identification and Orientation Detection for Indian Text Images

Composite Script Identification and Orientation Detection fo...

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International Conference on Document Analysis and recognition

作者： Shamita Ghosh Bidyut B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

A major preprocessing step in a multi-script OCR is to identify the script type of the test document image. The published papers on script identification usually assume that the test image is in correct i.e. 0° orientation. But by mistake a document may be fed to the system in wrong orientation, say at an angle of nearly 180° or ±90°. In this method we propose a script identification method that works for unknown orientation for all 11 official Indian scripts. Here, we first find the skew and counter-rotate the document by the skew angle. This will lead to correct (0°) or upside down (180°) orientation. Then script identification is done by a multi-stage tree classifier using features invariant to 0°/180° orientation. Next we go to find the orientation of the image by a two class classifier for each script. Performance of the proposed method has been tested on a variety of documents and promising results have been obtained.

关键词： Reservoirs Support vector machines Accuracy Feature extraction pattern recognition Kernel

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Automatic separation of machine-printed and hand-written text lines

Automatic separation of machine-printed and hand-written tex...

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International Conference on Document Analysis and recognition

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

There are many types of documents where machine-printed and hand-written texts appear intermixed. Since the optical character recognition (OCR) methodologies for machine-printed and hand-written texts are different, it is necessary to separate these two types of text before feeding them to the respective OCR systems. In this paper, we present such a scheme for both Bangla and Devnagari characters. The scheme is based on the structural and statistical features of the machine-printed and hand-written text lines. The classification scheme has an accuracy of about 98.3%.

关键词： Natural languages Optical character recognition software Neural networks computer vision pattern recognition Statistics Handwriting recognition Image segmentation Data mining Histograms

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Towards Indian language spell-checker design

Towards Indian language spell-checker design

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Language Engineering Conference

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

This paper deals with the development of a spell-checker in Indian languages using as an example Bangla, the second most popular language on the Indian Subcontinent. A brief review of problems and the current scenario of Indian language spell-checkers is described. The approach for the Bangla spell-checker is then elaborated. In this approach the technique works in two stages. The first stage takes care of phonetic similarity error. For that the phonetically similar characters are mapped into single units of character code. A new dictionary D/sub c/ is constructed with this reduced set of alphabets. A phonetically similar but wrongly spelt word can be easily corrected using this dictionary. The second stage takes care of errors other than phonetic similarity. A wrongly spelt word S of n characters is searched in the dictionary D/sub c/. If S is a nonword, its first k/sub 1//spl les/n characters will match with a valid word in D/sub c/. (if k/sub 1/=n then the word in D/sub c/ must be longer than n). A reversed word dictionary D/sub r/ is also generated where the characters of the word are maintained in a reversed order. If the last k/sub 2/ characters of S match with a word in D/sub r/ then, for a single error, it is located within the intersection region of first k/sub 1/+1 and last k/sub 2/+1 characters of S. We observed that this region is very small compared to word length for most cases and the number of suggested correct words can be drastically reduced using this information. We have used our approach in correcting Bangla text, where the problem of inflection is tackled by a simplified version of a morphological analyser. Another problem encountered in Indian languages is the existence of a large number of compound words formed by euphony and assimilation. The problem of compound words is also carefully tackled.

关键词： computer errors Dictionaries Optical character recognition software Error correction Optical computing pattern recognition computer interfaces Information retrieval Speech recognition computer vision

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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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Indian language multimedia and information retrieval

Indian language multimedia and information retrieval

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International Conference on Computational Intelligence and Multimedia Applications

作者： B.B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India

Over the last decade or so, remarkable developments in computer technology have given a major impetus to research in the field of multimedia. With the proliferation of the Internet and the increasingly widespread use of sophisticated computers, the multimedia revolution has arrived in India as well. It is therefore time to take stock of the situation: to evaluate how existing techniques can be used in the Indian context and to determine what new methods have to be developed. This paper summarizes the current state of multimedia technology in India and points to directions for further work. As more and more people in India begin to use computers and the Internet, multimedia capabilities will start playing a vital role in solving problems in many different areas. Education is probably one of the most important areas where multimedia technology can have a major impact. Already, multimedia educational systems are being developed in Indian languages. Several interactive encyclopaedia-like environments are also being marketed on CD-ROMs, and cover topics ranging from Indian classical music to Indian history, using text, images and sound. Some of the other possible applications of multimedia technology are: the development of digital libraries, news and information dissemination services, medicine, business and commerce, and the entertainment industry. Multimedia information technology is thus poised to become an exciting area for research and development activities in India.

关键词： Information retrieval Internet computer science education Educational technology Multimedia systems Music History Software libraries Biomedical imaging Business

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Multi-gradient-direction based deep learning model for arecanut disease identification

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CAAI Transactions on Intelligence Technology 2022年第2期7卷 156-166页

作者： S.B.Mallikarjuna Palaiahnakote Shivakumara Vijeta Khare M.Basavanna Umapada Pal B.Poornima Department of Computer Science and Engineering Bapuji Institute of Engineering and TechnologyDavanagereAffiliated to Visvesvaraya Theological UniversityBelagaviKarnatakaIndia Faculty of Computer Science and Information Technology University of MalayaKuala LumpurMalaysia Adani Institute of Infrastructure Engineering AhmedabadIndia Department of Computer Science Davanagere UniversityDavanagereKarnatakaIndia Computer Vision and Pattern Recognition Unit Indian Statistical InstituteKolkataWest BengalIndia

Arecanut disease identification is a challenging problem in the field of image *** this work,we present a new combination of multi-gradient-direction and deep con-volutional neural networks for arecanut disease identification,namely,rot,split and *** to the effect of the disease,there are chances of losing vital details in the *** enhance the fine details in the images affected by diseases,we explore multi-Sobel directional masks for convolving with the input image,which results in enhanced *** proposed method extracts arecanut as foreground from the enhanced images using Otsu ***,the features are extracted for foreground information for disease identification by exploring the ResNet *** advantage of the proposed approach is that it identifies the diseased images from the healthy arecanut *** results on the dataset of four classes(healthy,rot,split and rot-split)show that the proposed model is superior in terms of classification rate.

关键词： deep learning image analysis pattern recognition

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A word association based approach for improving retrieval performance from noisy OCRed text 6

A word association based approach for improving retrieval pe...

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6th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2014

作者： Chakraborty, Anirban Ghosh, Kripabandhu Roy, Utpal Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata700108 India Department of Computer and System Sciences Siksha-Bhavana Visva-Bharati Santiniketan731235 India

ISBN: (纸本)9789897580482

OCR errors hurt retrieval performance to a great extent. Research has been done on modelling and correction of OCR errors. However, most of the existing systems use language dependent resources or training texts for studying the nature of errors. Not much research has been reported on improving retrieval performance from erroneous text when no training data is available. We propose an algorithm of detecting OCR errors and improving retrieval performance from the erroneous corpus. We present two versions of the algorithm: one based on word cooccurrence and the other based on Pointwise Mutual Information. Our algorithm does not use any training data or any language specific resources like thesaurus. It also does not use any knowledge about the language except that the word delimiter is a blank space. We have tested our algorithm on erroneous Bangla FIRE collection and obtained significant improvements. Copyright © 2014 SCITEPRESS - Science and Technology Publications All rights reserved.

关键词： Errors

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An improved backpropagation neural network for detection of road-like features in satellite imagery

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INTERNATIONAL JOURNAL OF REMOTE SENSING 1997年第16期18卷 3379-3394页

作者： Bhattacharya, U Parui, SK Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta 700035 203 B. T. Road India

This paper presents an application of backpropagation neural network for the detection of linear structures in remote-sensing images. The purpose of the approach is two-fold. First, to exploit the advantages of a neural network classifier over the tranditional ones. Second, to avoid the strategic phases of enhancement and thresholding. Once the network is learnt, the classification scheme is real-time. Two critical issues in the present approach an the selection of the network architecture and the rate of convergence of learning. Solutions to these two problems are proposed. Experimental results on IRS and SPOT images are presented. Satisfactory classification results have been obtained using the network.

关键词： Remote sensing

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