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Texture features from Chaos Game Representation Images of Genomes
Vrinda V Nair, Nisha N. S., Vidya S., Y. S. Thushana
Pages - 183 - 190     |    Revised - 05-04-2013     |    Published - 30-04-2013
Volume - 7   Issue - 2    |    Publication Date - April 2013  Table of Contents
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KEYWORDS
Chaos Game Representation, Texture analysis, Wavelet decomposition, Support Vector Machines
ABSTRACT
The proposed work investigates the effectiveness of coarse measures of the Chaos Game Representation (CGR) images in differentiating genomes of various organisms. Major work in this area is seen to focus on feature extraction using Frequency Chaos Game Representation (FCGR) matrices. Although it is biologically significant, FCGR matrix has an inherent error which is associated with the insufficient computing as well as the screen resolutions. Hence the CGR image is converted to a texture image and corresponding feature vectors extracted. Features such as the texture properties and the subsequent wavelet coefficients of the texture image are used. Our work suggests that texture features characterize genomes well further; their wavelet coefficients yield better distinguishing capabilities.
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Professor Vrinda V Nair
Professor in ECE College of Engineering Trivandrum Thiruvananthapuram, Kerala - India
vrinda66nair@gmail.com
Miss Nisha N. S.
B.Tech student, College of Engineering Trivandrum Thiruvananthapuram, Kerala - India
Miss Vidya S.
B.Tech student, College of Engineering Trivandrum Thiruvananthapuram, Kerala - India
Miss Y. S. Thushana
B.Tech student, College of Engineering Trivandrum Thiruvananthapuram, Kerala - India