A TRANSITORY SURVEY OF TOPICAL TRENDS IN INDIC HANDWRITTEN CHARACTERS RECOGNITION

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Published: Oct 27, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i8.4791
Keywords:
Handwritten Character Recognition, Pre-processing, Feature Extraction, Classification, Zone segmentation

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GAUTAM .
Pondicherry University
K. VAITHEKI
Pondicherry University

Abstract

Handwritten Recognition, under pattern recognition, is a field having a diverse perspective in the present world scenario. A variety of handwritten text are needed to be recognized given the large quantity of offline and hard copy files need to be converted into a digitized format. An example of offline handwritten character recognition includes documents for office files, bank cheques, important reports and criminal and civil records files. However, for most of the languages that are common, i.e. English, it is particularly easy to convert images into textual data rather than any other scripts, which are complex. Of all the complex scripts, a particular script is known as Indic Scripts, which contains various scripts such a Devanagari, Bangla, Gurumukhi, Dravidian and such other scripts. In this paper, we present a survey of various Indic scripts and its recognition with respect to their corresponding approaches. We make a survey and present the comparative accuracy of several scripts belonging to Indic scripts.

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Vol. 8 No. 8 (2017): September-October
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Author Biographies

GAUTAM ., Pondicherry University

Student M.Tech (Computer Science and Engineering) Department of Computer Science School of Engineering and Technology Pondicherry University

K. VAITHEKI, Pondicherry University

Assistant Professor Department of Computer Science School of Engineering and Technology Pondicherry University

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