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Proceedings Paper

Adaptive approach for texture segmentation by multichannel wavelet frames
Author(s): Andrew F. Laine; Jian Fan
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Paper Abstract

We introduce an adaptive approach for texture feature extraction based on multi-channel wavelet frames and 2D envelope detection. Representations obtained from both standard wavelets and wavelet packets are evaluated for reliable texture segmentation. Algorithms for envelope detection based on edge detection and the Hilbert transform are presented. Analytic filters are selected for each technique based on performance evaluation. A K-means clustering algorithm was used to test the performance of each representation feature set. Experimental results for both natural textures and synthetic textures are shown.

Paper Details

Date Published: 1 November 1993
PDF: 12 pages
Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); doi: 10.1117/12.162071
Show Author Affiliations
Andrew F. Laine, Univ. of Florida (United States)
Jian Fan, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 2034:
Mathematical Imaging: Wavelet Applications in Signal and Image Processing
Andrew F. Laine, Editor(s)

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