1 research outputs found
Spectral Analysis of Projection Histogram for Enhancing Close matching character Recognition in Malayalam
The success rates of Optical Character Recognition (OCR) systems for printed
Malayalam documents is quite impressive with the state of the art accuracy
levels in the range of 85-95% for various. However for real applications,
further enhancement of this accuracy levels are required. One of the bottle
necks in further enhancement of the accuracy is identified as close-matching
characters. In this paper, we delineate the close matching characters in
Malayalam and report the development of a specialised classifier for these
close-matching characters. The output of a state of the art of OCR is taken and
characters falling into the close-matching character set is further fed into
this specialised classifier for enhancing the accuracy. The classifier is based
on support vector machine algorithm and uses feature vectors derived out of
spectral coefficients of projection histogram signals of close-matching
characters