Texture classification using wavelet transform

Authors:
S. Arivazhagan;L. Ganesan
Affiliations:
Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Amathur (P.O.), Sivakasi 626 005, India;Department of Computer Science and Engineering, Government College of Engineering, Tirunelveli 627 007, India
Venue:
Pattern Recognition Letters
Year:
2003

Citing 16
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Abstract

Today, texture analysis plays an important role in many tasks, ranging from remote sensing to medical imaging and query by content in large image data bases. The main difficulty of texture analysis in the past was the lack of adequate tools to characterize different scales of textures effectively. The development in multi-resolution analysis such as Gabor and wavelet transform help to overcome this difficulty. This paper describes the texture classification using (i) wavelet statistical features, (ii) wavelet co-occurrence features and (iii) a combination of wavelet statistical features and co-occurrence features of one level wavelet transformed images with different feature databases. It is found that, the results of later method are promising.