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Showing papers on "Devanagari published in 2005"


Proceedings ArticleDOI
31 Aug 2005
TL;DR: A system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts by using structural recognition techniques to reduce some characters to others and classified using the subspace method.
Abstract: In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system is evaluated for the writer dependent scenario.

87 citations


Proceedings ArticleDOI
31 Aug 2005
TL;DR: A sophisticated method for accurate zone detection in images of printed Gujarati is proposed and it is expected that this approach shall make the way smoother for the design and development of Gujarati OCR systems for complete character sets.
Abstract: Gujarati, is a language from the Indo-Aryan family of languages, used by 50 million people in the western part of India. Gujarati-script used to write the Gujarati language, is a multilevel script, written in three zones: base character zone, upper modifier zone and lower modifier zone. Several characters are discriminated by the specific modifiers, which exist in the upper and lower zones. Hence, detecting the zone boundaries is an important task in the Gujarati OCR. Although the Gujarati script is in some respects related to the Devanagari script, there are certain peculiar differences, which prevent the use of already known techniques for zone boundary detection for scripts such as Bengali, Assamese and Devanagari where mature OCR systems already do exist. There is only one previous documented effort for Gujarati OCR, in which an approach to recognize a small subset of Gujarati alphabet was discussed. The present paper proposes a sophisticated method for accurate zone detection in images of printed Gujarati. It is expected that this approach shall make the way smoother for the design and development of Gujarati OCR systems for complete character sets.

47 citations


Proceedings ArticleDOI
31 Aug 2005
TL;DR: This paper outlines the implementation of a neural network based Devanagari OCR and experimental results on a standard data set are reported and analyzed.
Abstract: OCR of Devanagari script presents a wide range of challenges that are not seen in Latin based scripts. This paper outlines the implementation of a neural network based Devanagari OCR. Experimental results on a standard data set are reported and analyzed.

38 citations


Book ChapterDOI
15 Dec 2005
TL;DR: Experimental results show the validity and efficiency of the developed scheme for recognition of characters of this script, and the major challenge in developing the proposed scheme lay in striking the right balance between definiteness and flexibility to derive optimal solutions for out of sample data.
Abstract: In this paper, a Devanagari script recognition scheme based on a novel algorithm is proposed. Devanagari script poses new challenges in the field of pattern recognition primarily due to the highly cursive nature of the script seen across its diverse character set. In the proposed algorithm, the character is initially subjected to a simple noise removal filter. Based on a reference co-ordinate system, the significant contours of the character are extracted and characterized as a contour set. The recognition of the character involves comparing these contour sets with those in the enrolled database. The matching of these contour sets is achieved by characterizing each contour based on its length, its relative position in the reference co-ordinate system and an interpolation scheme which eliminates displacement errors. In the Devanagari script, similar contour sets are observed among few characters, hence this method helps to filter out disparate characters and narrow down the possibilities to a limited set. The next step involves focusing on the subtle yet vital differences between the similar contours in this limited set. This is done by a prioritization scheme which concentrates only on those portions of character which reflect its uniqueness. The major challenge in developing the proposed scheme lay in striking the right balance between definiteness and flexibility to derive optimal solutions for out of sample data. Experimental results show the validity and efficiency of the developed scheme for recognition of characters of this script.

9 citations


DOI
01 Jan 2005
TL;DR: In this paper, the authors examine the ways in which the Devanagari script has, and has not, been adapted to the phonologies of the six languages of the Tibeto-Burman languages of Nepal.
Abstract: In this paper, the author is concerned primarily with two problems, specifically with respect to the 100+ Tibeto-Burman languages of Nepal and the attempts to write these languages with the Devanagari script. It is not attempt to survey all these languages; rather, he reports on six which have only recently come to be written with the Devanagari script: Chantyal, Gurung, Limbu, Sherpa, Tamang, and Thangmi. These languages constitute a rough-and-ready sample of the Tibeto-Burman languages of Nepal without a tradition of writing in the Devanagari script: some are locally prominent languages with large numbers of speakers, others more obscure; some have traditions of writing in scripts other than Devanagari, others do not. For none of these languages is there a fully standardized orthography, and none of these languages has been written in the Devanagari script in any serious way until quite recently. The goal of this paper is to examine the ways in which the Devanagari script has, and has not, been adapted to the phonologies of the six languages. The author first discusses the orthographic histories of each language, then the characteristics of the Devanagari script and the phonological system it is designed to accommodate. Later he presents brief sketches of the phonological inventories of the six languages, following by a discussion of how the script has — and has not — been adapted to accommodate these sound systems. The last section discusses the issue of ‘superfluous graph-emes’, and finish up with some concluding remarks on how Devanagari has been — and could be — adapted for these languages.

4 citations