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An OCR system to read two Indian language scripts: Bangla and Devnagari (Hindi)

An OCR system to read two Indian language scripts: Bangla an...

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International Conference on Document Analysis and recognition

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

An OCR system is proposed that can read two Indian language scripts: Bangla and Devnagari (Hindi), the most popular ones in the Indian subcontinent. These scripts, having the same origin in ancient Brahmi script, have many features in common and hence a single system can be modeled to recognize them. In the proposed model, document digitization, skew detection, text line segmentation and zone separation, word and character segmentation, character grouping into basic, modifier and compound character category are done for both scripts by the same set of algorithms. The feature sets and classification tree as well as the knowledge base required for error correction (such as lexicon) differ for Bangla and Devnagari. The system shows a good performance for single font scripts printed on clear documents.

关键词： Optical character recognition software Natural languages Error correction Character recognition Switches computer vision pattern recognition Cleaning Text recognition Writing

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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 syntactic approach for processing mathematical expressions in printed documents

A syntactic approach for processing mathematical expressions...

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International Conference on pattern recognition

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

ISBN: (纸本)0769507506

We propose an approach for understanding mathematical expressions in printed documents. The overall approach is divided into three main steps: (i) detection of mathematical expressions in a document, (ii) recognition of the symbols present in the expression and (iii) arrangement of the recognized symbols. The detection of mathematical expressions is done through recognition of a few most common symbols and exploiting some structural features of the expressions. A hybrid of feature based and a template-based technique is used for the recognition of symbols. A two-pass approach is used for arrangement of the symbols. The first pass (scanning or lexical analysis) performs a micro-level examination of the symbols in order to identify the symbol groups occurring in them and to determine their categories or descriptors. The second pass (parsing or syntax analysis) processes the descriptors synthesized in the first pass, to determine the syntactic structure of the expression. A set of predefined rules guides the activities in both the passes. Experiments conducted using this approach on a large number of documents show high accuracy.

关键词： Optical character recognition software computer vision pattern recognition Performance analysis Equations Document handling Testing Books White spaces

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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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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri T.T. Pal Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)076951695X

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 was designed and the proposed similarity measure appears to be quite robust against wide variations in writing styles. Initially, the approach was 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: 97.29% for Devnagari and 96.34% for Bangla.

关键词： Handwriting recognition Humans Character recognition pattern recognition Keyboards computer vision Writing Job design Feature extraction Algorithm design and analysis

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Automatic recognition of printed Oriya script

Automatic recognition of printed Oriya script

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International Conference on Document Analysis and recognition

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

ISBN: (纸本)0769512631

The paper deals with an optical character recognition system for printed Oriya, a popular Indian script. The development of OCR for this script is difficult because a large number of characters have to be recognized. In the proposed system, the digitized document image is first passed through preprocessing modules like skew correction, line segmentation, zone detection, word and character segmentation, etc. These modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of a water reservoir. The feature detection methods are simple and robust. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.

关键词： Character recognition Optical character recognition software Image segmentation Water resources Reservoirs computer vision Robustness Prototypes Materials testing System testing

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Automatic identification of English, Chinese, Arabic, Devnagari and Bangla script line

Automatic identification of English, Chinese, Arabic, Devnag...

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International Conference on Document Analysis and recognition

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

In a general situation, a document page may contain several scriptforms. For optical character recognition (OCR) of such a document page, it is necessary to separate the scripts before feeding them to their individual OCR systems. An automatic technique for the identification of printed Roman, Chinese, Arabic, Devnagari and Bangla text lines from a single document is proposed. Shape based features, statistical features and some features obtained from the concept of a water reservoir are used for script identification. The proposed scheme has an accuracy of about 97.33%.

关键词： Water resources Reservoirs Optical character recognition software Shape Water storage Probability computer vision pattern recognition Optical devices Fractals

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An approach for stemming in symbolically compressed Indian language imaged documents

An approach for stemming in symbolically compressed Indian l...

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International Conference on Document Analysis and recognition

作者： U. Garain A.K. Datta Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots, and thereby improving the overall retrieval efficiency. This paper presents an algorithm for stemming in the context of document image retrieval system. The algorithm assumes that the documents are symbolically compressed and stemming has been attempted in the compressed domain itself. Experiments have been conducted on Indian language imaged documents for which efficient OCR still remains a challenging task. Results obtained from a set 150 document images (in Bangla script, the second most popular script in the Indian sub-continent) consisting of about 12K word show a promising performance of the proposed approach.

关键词： Image coding Image retrieval Optical character recognition software Information retrieval Internet Image storage computer vision pattern recognition Search engines Character recognition

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Script line separation from Indian multi-script documents

Script line separation from Indian multi-script documents

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International Conference on Document Analysis and recognition

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

In a multi-lingual country like India, a document page may contain more than one script form. Under the three-language formula, the document may be printed in English, Devnagari and one of the other official Indian languages. For OCR of such a document page, it is necessary to separate these three script forms before feeding them to the OCRs of individual scripts. In this paper, an automatic technique of separating the text lines using script characteristics and shape based features is presented. At present, the system has an overall accuracy of about 98.5%.

关键词： Natural languages Optical character recognition software Shape Optical filters computer vision pattern recognition Writing Read only memory Character generation

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A New Defect Detection Method for Improving Text Detection and recognition Performances in Natural Scene Images

A New Defect Detection Method for Improving Text Detection a...

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2020 Swedish Workshop on Data Science, SweDS 2020

作者： Mokayed, Hamam Shivakumara, Palaiahnakote Liwicki, Marcus Pal, Umapada University of Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia Lulea University of Technology Department of Computer Science Electrical and Space Engineering Sweden Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

ISBN: (纸本)9781728192048

This paper presents a new idea for improving text detection and recognition performances by detecting defects in the text detection results. Despite the rapid development of powerful deep learning based models for scene text detection and recognition in the wild, in complex situations (logos or decorated components connected with text), existing methods do not yield satisfactory results. In this paper, we propose to use post-processing method to improve the text detection and recognition performance. The proposed method extracts features, namely phase congruency, entropy and compactness for the text detection results. To strengthen discriminative power for feature extraction, we explore the combination of SVM classifier and Gaussian distribution of text components to determine proper weight, which represents true text component. The weights are multiplied with the features to detect defect components though clustering. The bounding boxes are redrawn, which results proper bounding box without defects components. Experimental results show that the proposed defect detection reports satisfactory results. To validate the effectiveness of defect detection, we conduct experiments on benchmark datasets of MSRA-TD-500 and SVT for detection and recognition before and after defect detection. The result shows that the performance of text detection and recognition improves significantly after defect detection. © 2020 IEEE.

关键词： Gaussian distribution

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Convex hull based approach for multi-oriented character recognition from graphical documents

Convex hull based approach for multi-oriented character reco...

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作者： Roy, Partha Pratim Pal, Umapada Lladós, Josep Kimura, Fumitaka Computer Vision Center Universitat Autònoma De Barcelona 08193 Bellaterra Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata - 108 India Graduate School of Engineering Mie University 1577 Kurimamachiya Mie 514-8504 Japan

ISBN: (纸本)9781424421756

In this paper, we present a scheme towards recognition of English character in multi-scale and multi-oriented environments. Graphical document such as map consists of text lines which appear in different orientation. Sometimes, characters in a single word may follow a curvi-linear way to annotate the graphical curve lines. For recognition of such multi-scale and multi-oriented characters a Support Vector Machine (SVM) based scheme is presented in this paper. The feature used here is invariant to character orientation. Circular ring and convex hull have been used along with angular information of the contour pixels of the character to make the feature rotation invariant. We tested our proposed scheme on two different datasets. Combining circular and convex hull feature we have obtained 96.73% and 99.56% accuracy in these two datasets. © 2008 IEEE.

关键词： Support vector machines

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