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Proceedings Paper

Hierarchical texture segmentation with wavelet packet transform and adaptive smoothing
Author(s): Yu-Chuan Lin; Tianhorng Chang; C.-C. Jay Kuo
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Paper Abstract

A new texture segmentation algorithm based on the wavelet transform and a hierarchical fuzzy processing technique is proposed in this research. We perform a tree-structured wavelet transform to decompose a textured image adaptively into subimages corresponding to different frequency channels, and assign a fuzzy membership function to every spatial location by examining the averaged energy value of a local window centered at that point. A procedure to determine the proper smoothing window size is described. The fuzzy membership function in different subimages is then integrated hierarchically to lead to the final segmentation result. Numerical experiments are given to demonstrate the performance of our proposed algorithm.

Paper Details

Date Published: 16 September 1994
PDF: 12 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185951
Show Author Affiliations
Yu-Chuan Lin, Univ. of Southern California (United States)
Tianhorng Chang, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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