Adaptive approach for texture segmentation by multichannel wavelet frames

Andrew F. Laine; Jian Fan

doi:10.1117/12.162071

1 November 1993 Adaptive approach for texture segmentation by multichannel wavelet frames

Andrew F. Laine, Jian Fan

Proceedings Volume 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing; (1993) https://doi.org/10.1117/12.162071
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

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.

Citation Download Citation

Andrew F. Laine and Jian Fan "Adaptive approach for texture segmentation by multichannel wavelet frames", Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); https://doi.org/10.1117/12.162071

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