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2nd International Workshop on Automated Forensic Handwriting Analysis, AFHA 2013

作者： Pal, Srikanta Pal, Umapada Blumenstein, Michael School of Information and Communication Technology Griffith University Gold Coast Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Signature identification and verification are of great importance in authentication systems. The purpose of this paper is to introduce an experimental contribution in the direction of multi-script off-line signature identification and verification using a novel technique involving off-line English, Hindi (Devnagari) and Bangla (Bengali) signatures. In the first evaluation stage of the proposed signature verification technique, the performance of a multi-script off-line signature verification system, considering a joint dataset of English, Hindi and Bangla signatures, was investigated. In the second stage of experimentation, multi-script signatures were identified based on the script type, and subsequently the verification task was explored separately for English, Hindi and Bangla signatures based on the identified script result. The gradient and chain code features were employed, and Support Vector Machines (SVMs) along with the Modified Quadratic Discriminate Function (MQDF) were considered in this scheme. From the experimental results achieved, it is noted that the verification accuracy obtained in the second stage of experiments (where a signature script identification method was introduced) is better than the verification accuracy produced following the first stage of experiments. Experimental results indicated that an average error rate of 20.80% and 16.40% were obtained for two different types of verification experiments.

关键词： Support vector machines

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Fine classification of unconstrained handwritten Persian/Arabic numerals by removing confusion amongst similar classes

Fine classification of unconstrained handwritten Persian/Ara...

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ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9780769537252

In this paper, we propose two types of feature sets based on modified chain-code direction frequencies in the contour pixels of input image and modified transition features (horizontally and vertically). A multi-level support vector machine (SVM) is proposed as classifier to recognize Persian isolated digits. In first level, we combine similar shaped numerals into a single group and as result;we obtain 7 classes instead of 10 classes. We compute 196-dimension chain-code direction frequencies as features to discriminate 7 classes. In the second level, classes containing more than one numeral because of high resemblance in their shapes are considered. We use modified transition features (horizontally and vertically) for discriminating between two overlapping classes (0 and 1). To separate another overlapping group containing three numerals 2, 3 and 4 we first eliminate common parts of these digits (tail) and then compute chain code features. We employ SVM classifier for the classification and evaluate our scheme on 80,000 handwritten samples of Persian numerals [10]. Using 60,000 samples for training, we tested our scheme on other 20,000 samples and obtained 99.02% accuracy. © 2009 IEEE.

关键词： Support vector machines

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Word-wise Thai and Roman script identification

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ACM Transactions on Asian Language Information Processing 2009年第3期8卷 1–21页

作者： Chanda, Sukalpa Pal, Umapada Terrades, Oriol Ramos Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkatta-700108 India Instituto Tecnologico de Informatica Univ. Politécnica de Valencia 46022 Valencia Spain

In some Thai documents, a single text line of a printed document page may contain words of both Thai and Roman scripts. For the Optical Character recognition (OCR) of such a document page it is better to identify, at first, Thai and Roman script portions and then to use individual OCR systems of the respective scripts on these identified portions. In this article, an SVM-based method is proposed for identification of word-wise printed Roman and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of a character group combining different character features obtained from structural shape, profile behavior, component overlapping information, topological properties, and water reservoir concept, etc. Based on the experiment on 10,000 data (words) we obtained 99.62% script identification accuracy from the proposed scheme. © 2009 ACM.

关键词： Optical character recognition

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Shape code based word-image matching for retrieval of indian multi-lingual documents

Shape code based word-image matching for retrieval of Indian...

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International Conference on pattern recognition

作者： Tarafdar, Arundhati Mondal, Ranju Pal, Srikanta Pal, Umapada Kimura, Fumitaka Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India Graduate School of Engineering Mie University Kurimamachiya-cho Tsu Japan

ISBN: (纸本)9780769541099

In the current scenario retrieving information from document images is a challenging problem. In this paper we propose a shape code based word-image matching (words-potting) technique for retrieval of multilingual documents written in indian languages. Here, each query word image to be searched is represented by a primitive shape code using (i) zonal information of extreme points (ii) vertical shape based feature (iii) crossing count (with respect to vertical bar position) (iv) loop shape and position (v) background information etc. Each candidate word (a word having similar aspect ratio and topological feature to the query word) of the document is also coded accordingly. Then, an inexact string matching technique is used to measure the similarity between the primitive codes generated from the query word image and each candidate word of the document with which the query image is to be searched. Based on the similarity score, we retrieve the document where the query image is found. Experimental results on Bangla, Devnagari and Gurumukhi scripts document image databases confirm the feasibility and efficiency of our proposed approach. © 2010 IEEE.

关键词： Image matching

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Complete statistical Analysis to Weather Forecasting 1st

Complete Statistical Analysis to Weather Forecasting

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1st International Conference on Computational Intelligence in pattern recognition, CIPR 2019

作者： Datta, Anisha Si, Shukrity Biswas, Sanket Department of Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri735102 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9789811390418

The primary objective of the model applied in this work is to predict the weather of a city named Austin in Texas using supervised machine learning algorithms. In this case, artificial neural networks and gradient boosting classifier were implemented to build models to predict weather and comparisons between these two models are also made for this dataset. Here, average temperature, average dew point, average pressure of sea level, average percentage of humidity, etc. are the parameters taken into consideration which influence the weather of the place. Using these parameters, the trained models performed a classification to predict whether the weather is rainy (thunderstorm or not), not rainy, snowy, or foggy. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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A robust block oriented watermarking scheme in spatial domain 1

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4th International Conference on Information and Communications Security, ICICS 2002

作者： Das, Tanmoy Kanti Maitra, Subhamoy Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B T Road Calcutta700 108 India Applied Statistics Unit Indian Statistical Institute 203 B T Road Calcutta700 108 India

In this paper we present an invisible spatial domain watermarking technique. The technique divides the image into n small blocks and the intensity of some of these blocks are modified depending on the key, which is a ... 详细信息

ISBN: (数字)9783540361596

ISBN: (纸本)3540001646

关键词： Frequency domain analysis

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Off-line Bangla signature verification

Off-line Bangla signature verification

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10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Pal, Srikanta Nguyen, Vu Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University Gold Coast QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9780769546612

In the field of information security, biometric systems play an important role. Within biometrics, automatic signature identification and verification has been a strong research area because of the social and legal acceptance and extensive use of the written signature as an individual authentication. Signature verification is a process in which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite substantial research in the field of signature verification involving Western signatures, very few works have been dedicated to non-Western signatures such as Chinese, Japanese, Arabic, or Persian etc. In this paper, the performance of an off-line signature verification system involving Bangla signatures, whose style is distinct from Western scripts, was investigated. The Gaussian Grid feature extraction technique was employed for feature extraction and Support Vector Machines (SVMs) were considered for classification. The Bangla signature database employed in the experiments consisted of 3000 forgeries and 2400 genuine signatures. An encouraging accuracy of 90.4% was obtained from the experiments. © 2012 IEEE.

关键词： Biometrics

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Cryptanalysis of optimal differential energy watermarking (DEW) and a modified robust scheme 3rd

Cryptanalysis of optimal differential energy watermarking (D...

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3rd International Conference on Cryptology in India, INDOCRYPT 2002

ISBN: (纸本)9783540362319

In this paper we provide a cryptanalysis of the well known "Optimal Differential Energy Watermarking (DEW)" scheme. The DEW scheme divides the image into some disjoint regions (each region containing two subregions). The watermark is basically a secret binary string where each individual bit information is inserted in one of the regions by modifying the high frequency DCT (Discrete Cosine Transform) coefficients. This modification creates required energy difference between two subregions. We here modify the high frequency components so that this energy difference vanishes and in turn extraction of watermark signal becomes impossible, making the cryptanalysis successful. Moreover, we modify the DEW scheme by inserting the bit information in low frequency components instead of high frequency components and propose an oblivious robust watermarking strategy which can trace the buyer too. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Discrete cosine transforms

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Comparative study of Devnagari handwritten character recognition using different feature and classifiers

Comparative study of Devnagari handwritten character recogni...

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ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Pal, U. Wakabayashi, T. Kimura, F. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India Graduate School of Engineering Mie University TSU Mie 514-8507 Japan

ISBN: (纸本)9780769537252

In recent years research towards indian handwritten character recognition is getting increasing attention. Many approaches have been proposed by the researchers towards handwritten indian character recognition and many recognition systems for isolated handwritten numerals/characters are available in the literature. To get idea of the recognition results of different classifiers and to provide new benchmark for future research, in this paper a comparative study of Devnagari handwritten character recognition using twelve different classifiers and four sets of feature is presented. Projection distance, subspace method, linear discriminant function, support vector machines, modified quadratic discriminant function, mirror image learning, Euclidean distance, nearest neighbour, k-Nearest neighbour, modified projection distance, compound projection distance, and compound modified quadratic discriminant function are used as different classifiers. Feature sets used in the classifiers are computed based on curvature and gradient information obtained from binary as well as gray-scale images. © 2009 IEEE.

关键词： Character recognition

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Online handwritten indian script recognition: A human motor function based framework

Online handwritten Indian script recognition: A human motor ...

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作者： Garain, U. Chaudhuri, B.B. Pal, T.T. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata 700 108 India

This paper presents the online handwriting recognition for indian scripts. The primary concern of the approach is the modeling of human motor functionality while writing characters. This is achieved by looking at the whole pen trajectory where the time evaluation of the pen coordinates plays a crucial role. A low complexity classifier has been designed and the proposed similarity measure appears to be quite robust against wide variations in writing styles. Initially, the approach has been applied for online recognition of handwritten characters in Devnagari and Bangla, the two major indian scripts. A test on a dataset of considerable size shows promising recognition rates namely, 97.29% for Devnagari and 96.34% for Bangla. © 2002 IEEE.

关键词： pattern recognition

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