Abstract—Abstract—Wavelet theory is one of the greatest achievements of last decade. The results produced by wavelet based analysis have really astonished the modern research communities in various fields. Wavelet based analysis is still an active research area due to its tremendous variety of applications. This paper provides the comparative analysis of various wavelet transforms to recognize ancient Grantha script. Grantha Script is an ancient script that is used in southern part of India to write Sanskrit language and the motivation of this work is to explore the hidden information from the ancient documents written in Grantha script. For the recognition of ancient Grantha script, a comparative analysis of various transforms like haar, biorthogonal, coiflet, daubechies, discrete meyer and symlet wavelet families are carried out. Discrete meyer wavelet produces the highest recognition efficiency compared to other wavelet families. In this work, the Feed Forward Neural network is used for classification purpose.
Index Terms—Index Terms—Biorthogonal, coiflet, daubachies, discrete meyer, grantha script, symlet.
Jyothi. R. L is with College of Engineering, Karunagapally. She is undergoing her Ph.D at Kerala University, India (e-mail: jyothianil@gmail.com)
Abdul Rahiman M. is with Kerala Technological University. He is the research guide under faculty of Engineering in Kerala University, India (e-mail: rahiman_paika@gmail.com).
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Cite:Jyothi R. L. and Abdul Rahiman M., "Comparative Analysis of Wavelet Transforms in the Recognition of Ancient Grantha Script," International Journal of Computer Theory and Engineering vol. 9, no. 4, pp. 235-241, 2017.
