Wavelet based Texture Segmentation

Author

Wilscy, M. ; Sasi, Remya K.

Author_Institution

Dept. of Comput. Sci., Univ. of Kerala, Thiruvananthapuram, India

fYear

2010

fDate

28-29 Dec. 2010

Firstpage

1

Lastpage

4

Abstract

Hierarchical Texture Segmentation using Wavelet packet decomposition performs an unsupervised classification of Texture features, extracted using wavelet packet decomposition to generate a segmented image. Recursive decomposition of both the approximation and the detail coefficients derived from the original signal provides a wider spectrum for richer feature extraction. This Texture Segmentation works well for Texture images with only two Textures. This approach can be used for shape extraction, detecting industrial defects, and for text extraction.

Keywords

feature extraction; image classification; image segmentation; image texture; unsupervised learning; wavelet transforms; feature extraction; hierarchical texture segmentation; image texture; recursive decomposition; shape extraction; unsupervised classification; wavelet packet decomposition; wavelet-based texture segmentation; Clustering algorithms; Feature extraction; Image segmentation; Pixel; Wavelet packets; Segmentation; Texture; Wavelet Packet Decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4244-5965-0

Electronic_ISBN

978-1-4244-5967-4

Type

conf

DOI

10.1109/ICCIC.2010.5705877

Filename

5705877