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Reseach Article

Handwritten Script Recognition using DCT and Wavelet Features at Block Level

Published on None 2010 by G. G. Rajput, Anita H. B.
Recent Trends in Image Processing and Pattern Recognition
Foundation of Computer Science USA
RTIPPR - Number 3
None 2010
Authors: G. G. Rajput, Anita H. B.
b52807d1-6eeb-4f84-af60-ad89e2d55151

G. G. Rajput, Anita H. B. . Handwritten Script Recognition using DCT and Wavelet Features at Block Level. Recent Trends in Image Processing and Pattern Recognition. RTIPPR, 3 (None 2010), 158-163.

@article{
author = { G. G. Rajput, Anita H. B. },
title = { Handwritten Script Recognition using DCT and Wavelet Features at Block Level },
journal = { Recent Trends in Image Processing and Pattern Recognition },
issue_date = { None 2010 },
volume = { RTIPPR },
number = { 3 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 158-163 },
numpages = 6,
url = { /specialissues/rtippr/number3/992-115/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Recent Trends in Image Processing and Pattern Recognition
%A G. G. Rajput
%A Anita H. B.
%T Handwritten Script Recognition using DCT and Wavelet Features at Block Level
%J Recent Trends in Image Processing and Pattern Recognition
%@ 0975-8887
%V RTIPPR
%N 3
%P 158-163
%D 2010
%I International Journal of Computer Applications
Abstract

In a country like India where different scripts are in use, automatic identification of handwritten script facilitates many important applications such as automatic transcription of multilingual documents and for the selection of script specific OCR in a multilingual environment. Existing script identification techniques depend on various features extracted from document images at character, word, text line or block level. In this paper, we propose a novel method towards multi-script identification at block level. The recognition is based upon features extracted using Discrete Cosine Transform (DCT) and Wavelets of Daubechies family. The proposed method is experimented on handwritten documents of eight Indian scripts that include English script and yielded encouraging results.

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Index Terms

Computer Science
Information Sciences

Keywords

Multi-script documents handwritten script Discrete Cosine Transform Wavelets K-NN classifier