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Detection of structural concavities in character images - A writer-independent approach
S. Bag, P. Bhowmick,
Published in
Volume: 7143 LNCS
Pages: 260 - 268
In this paper, we present a novel technique for detection of concave regions as a structural information of character images. The problem difficulty lies in reporting all concavities irrespective of the viewing direction on the 2D plane. In our approach, we detect concave regions by analyzing the sequence of discrete turns taken to describe the character stroke; hence, it becomes view-invariant. The proposed method has the added advantage of detecting same concave regions of a particular character written by different individuals. We have tested our method on printed and handwritten Bangla and Hindi isolated character images. Initial results demonstrate the efficacy of our approach. © 2012 Springer-Verlag.
About the journal
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)