Digital Image Processing

R. Paul Jeba Kumar ¹, C. Akila ², R. Mercy ², M. Deepa Lakshmi ³

Affiliations
1 Anna University, Tirunelveli, IN
2 Department in CSE, Anna University, Tirunelveli, IN
3 PSNCET, Tirunelveli, IN

Abstract

This paper describes effective texture characterization techniques using wavelet packet decompositions. The proposed work presents a statistical view of the image classification problem by combining the tasks, namely feature extraction (FE) and similarity measurement (SM), into a joint modeling and classification scheme. The proposed method uses the wavelet packet energy as a feature for texture classification for a compact feature representation and better classification accuracy. It shows that incorporating the sub band grouping and selection method and Fuzzy C Means algorithm improves the feature selection and classification accuracy. Experimental results on a database of texture images indicate that the new method significantly improves Classification rates compared with traditional approaches, while it retains comparable levels of computational complexity.

Keywords

Mutual Information, SGS, DWPT, FCM.

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