Unsupervised/supervised texture segmentation and its application to real-world data

Devesh Patel; T. John Stonham

doi:10.1117/12.131392

1 November 1992 Unsupervised/supervised texture segmentation and its application to real-world data

Devesh Patel, T. John Stonham

Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992) https://doi.org/10.1117/12.131392
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

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.

Citation Download Citation

Devesh Patel and T. John Stonham "Unsupervised/supervised texture segmentation and its application to real-world data", Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); https://doi.org/10.1117/12.131392

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