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Proceedings Paper

Unsupervised/supervised texture segmentation and its application to real-world data
Author(s): Devesh Patel; T. John Stonham
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Paper Abstract

We present a texture segmentation technique which can be adapted for a broad category of applications. A Texture Co-occurrence Spectrum is generated for each texture sample by extracting information from all directions around a pixel. A Combined Unsupervised/Supervised clustering algorithm, then groups the Co-occurrence spectra in feature space into clusters representing homogeneous textured regions. The method as presented is applied to, and shown to be capable of segmenting natural texture composites and real-world images such as silica particle micrographs and aerial images.

Paper Details

Date Published: 1 November 1992
PDF: 12 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131392
Show Author Affiliations
Devesh Patel, Brunel Univ. (United Kingdom)
T. John Stonham, Brunel Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

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