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Coarse Classification of Handwritten Hindi Characters

By Pooja Agrawal, M. Hanm and Brejesh Lall

Abstract

This paper describes a system to classify the off-line handwritten Hindi characters into several groups based on some similarity measure. A novel method is proposed for finding the header line, based on end points and pixels positions in the top half part of the character image. The algorithm works in the presence of slant of the header line. After the identification and removal of header line, all the characters are coarse classified. A new algorithm is designed for the identification of presence and position of vertical bar in the handwritten Hindi characters. A coarse classification rate of 97.25 % has been achieved in the simulation study

Topics: Header line, Vertical bar, Handwritten Hindi characters, End points
Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.178.2096
Provided by: CiteSeerX
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