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Lexicon Reduction Technique for Bangla Handwritten Word recognition

Lexicon Reduction Technique for Bangla Handwritten Word Reco...

引用

IAPR International Workshop on Document Analysis Systems, DAS

作者： Tapan Kumar Bhowmik Utpal Roy Swapan K. Parui Faculty of Mathematics and Natural Sciences University of Groningam Netherlands Department of Computer and System Sciences Visva Bharati University Santiniketan India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In this paper we introduce a stroke based lexicon reduction technique in order to reduce the search space for recognition of handwritten words. The principle of this technique involves mainly two aspects of a word image to constitute a feature vector: one is word-length and the other is shape of the word. The length of the word image is represented by the number of specific vertical strokes present in the word image and, on the other hand, the shape of a word image is realized with the combination of both horizontal and vertical strokes. The experiment has been carried out with a database of 35,700 off-line handwritten Bangla word images. Though our proposed lexicon reduction technique is developed for recognition of Bangla handwritten words, its generalization property can easily be exploited for recognition of handwriting in other scripts also.

关键词： Handwriting recognition Hidden Markov models Shape Vectors Feature extraction Conferences

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Cursive Handwritten Segmentation and recognition for Instructional Videos

Cursive Handwritten Segmentation and Recognition for Instruc...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Ali Shariq Imran Sukalpa Chanda Faouzi Alaya Cheikh Katrin Franke Umapada Pal Dept. of Computer Science and Media Technology Gjϕvik University College Gjøvik Norway Hogskolen i Gjovik Gjovik Oppland NO Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In this paper, we address the issues pertaining to segmentation and recognition of cursive handwritten text from chalkboard lecture videos. Recognizing handwritten text is a challenging problem in instructor-led lecture video. The task gets even tougher with varying handwriting styles and blackboard type. Unlike handwritten text on whiteboard and electronic boards, chalkboard represents serious challenges such as, lack of uniform edge density, weak chalk contrast against blackboard and leftover chalk dust noise as a result of erasing -- and many others. Moreover, the varying color of boards and the illumination changes within the video makes it impossible to use trivial thresholding techniques, for the extraction of content. Many universities throughout the world still heavily rely on chalkboard as a mode of instruction. Therefore, recognizing these lecture content will not only aid in indexing and retrieval applications but will also help understand high level video semantics, useful for Multi-media Learning Objects (MLO). In order to encounter those adversaries, we here propose a system for segmentation and recognition of cursive handwritten text from chalkboard lecture videos. We first create a foreground model to segment background blackboard. We then segment the text characters using one-dimensional vertical histogram. Later, we extract gradient based features and classify those characters using an SVM classifier. We obtained an encouraging accuracy of 86.28% on 5-fold cross validation.

关键词： Videos Feature extraction Text recognition Support vector machines Databases Kernel Handwriting recognition

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ICFHR 2012 Competition on recognition of On-Line Mathematical Expressions (CROHME 2012)

ICFHR 2012 Competition on Recognition of On-Line Mathematica...

引用

International Workshop on Frontiers in Handwriting recognition

作者： Harold Mouchère Christian Viard-Gaudin D.H. Kim J.H. Kim U. Garain IRCCyN/IVC-UMR CNRS 6597 Ecole Polytechnique de l'Iniversité de Nantes France Division of Computer Science Korea Advanced Institute of Science and Technology South Korea Computer Vision and Pattern Recognition (CVPR) Unit Indian Statistical Institute India

This paper presents an overview of the second Competition on recognition of Online Handwritten Mathematical Expressions, CROHME 2012. The objective of the contest is to identify current advances in mathematical expression recognition using common evaluation performance measures and datasets. This paper describes the contest details including the evaluation measures used as well as the performance of the 7 submitted systems along with a short description of each system. Progress as compared to the 1st version of CROHME is also documented.

关键词： Handwriting recognition

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A new dataset of Persian handwritten documents and its segmentation

A new dataset of Persian handwritten documents and its segme...

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2011 7th Iranian Conference on Machine vision and Image Processing, MVIP 2011

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9781457715358

In document image analysis and especially in handwritten document image recognition, standard datasets play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. In this paper, an unconstrained Persian handwritten text dataset (PHTD) is introduced. The PHTD contains 140 handwritten documents of three different categories written by 40 individuals. Total number of text-lines and words/subwords in the dataset are 1787 and 27073, respectively. In most of the PHTD documents either an overlapping or a touching text-lines is present. The average number of text-lines in documents of the PHTD is 13. Two types of ground truths based on pixels information and content information are generated for the dataset. Providing these two types of ground truths for the PHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported. © 2011 IEEE.

关键词： Image segmentation

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Off-line signature verification systems: A survey 11

Off-line signature verification systems: A survey

引用

Proceedings of the International Conference & Workshop on Emerging Trends in Technology

作者： Pal, S. Blumenstein, M. Pal, U. School of Information and Communication Technology Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9781450304498

Signatures are extensively used as a means of personal verification. Manual signature-based authentication of a large number of documents is a very difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable physical unique characteristics (hand geometry, iris scan, finger prints or DNA) or behavioural features. Human signatures provide secure means for confirmation and authorization in legal documents. So nowadays, automatic signature verification becomes an essential component. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of off-line signature verification systems. Copyright © 2011 ACM.

关键词： Biometrics

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Non-english and non-latin signature verification systems: A survey

Non-english and non-latin signature verification systems: A ...

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1st International Workshop on Automated Forensic Handwriting Analysis, AFHA 2011 - A Satellite Workshop of ICDAR 2011

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

Signatures continue to be an important biometric because they remain widely used as a means of personal verification and therefore an automatic verification system is needed. Manual signature-based authentication of a large number of documents is a difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable unique physical characteristics (e.g. hand geometry, iris scan, finger prints or DNA) or behavioural features. Substantial research has been undertaken in the field of signature verification involving English signatures, but to the best of our knowledge, very few works have considered non-English signatures such as Chinese, Japanese, Arabic etc. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of non-English and non-Latin signature verification systems.

关键词： Biometrics

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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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Off-line signature identification using background and foreground information

Off-line signature identification using background and foreg...

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2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011

作者： Pal, Srikanta Alireza, Alaei Pal, Umapada Blumenstein, Michael School of Information and Communication Technology Griffith University Gold Coast QLD Australia Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9780769545882

Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. In this paper, a technique for a bi-script off-line signature identification system is proposed. In the proposed signature identification system, the signatures of English and Bengali (Bangla) are considered for the identification process. Different features such as under sampled bitmaps, modified chain-code direction features and gradient features computed from both background and foreground components are employed for this purpose. Support Vector Machines (SVMs) and Nearest Neighbour (NN) techniques are considered as classifiers for signature identification in the proposed system. A database of 1554 English signatures and 1092 Bengali signatures are used to generate the experimental results. Various results based on different features are calculated and analysed. The highest accuracies of 99.41%, 98.45%;and 97.75% are obtained based on the modified chain-code direction, under-sampled bitmaps and gradient features respectively using 1800 (1100 English+700 Bengali) samples for training and 846 (454 English+392 Bengali) samples for testing. © 2011 IEEE.

关键词： Biometrics

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A New Dataset of Persian Handwritten Documents and Its Segmentation

A New Dataset of Persian Handwritten Documents and Its Segme...

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Iranian Machine vision and Image Processing (MVIP)

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

关键词： Image segmentation Handwriting recognition Databases Character recognition Image recognition Text recognition

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A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents

A New Text-Line Alignment Approach Based on Piece-Wise Paint...

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International Conference on Document Analysis and recognition

Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In this paper, we propose a text-line alignment technique based on painting algorithm. Here at first, Piece-wise Painting Algorithm (PPA) is used to get a number of black and white rectangular patches all along the text-line for text-line alignment. Identifying the degree of oscillation of the input text-line, some candidate pixels are also obtained based on horizontal projection and center points of the black patches. Using the degree of oscillation of the input text image and the candidate pixels a curve or straight line is fit to trace the baseline. Subsequently, all components of the text-line are deskewed based on analyzing the characteristic of the fit curve or line to align the components with respect to the horizontal imaginary baseline. The proposed algorithm was evaluated with 128 Persian handwritten text-lines containing 4317 sub words. Experimental analysis showed that 92.31% of the sub words were accurately aligned. Further, the proposed algorithm was tested with another Persian handwritten text-lines dataset [6] and remarkable results were achieved.

关键词： Oscillators Painting Polynomials Algorithm design and analysis Curve fitting Estimation pattern recognition

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