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Proceedings Paper

A New Image Segmentation And Texture Analysis Algorithm
Author(s): Chester L. Richards Jr.
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Paper Abstract

Traditionally, image segmentation algorithms work by either making point amplitude measurements or by scanning a small computational window over the scene to discover local texture statistics. Where these measurements significantly change, the boundary of an object is said to exist. In this new image segmentation algorithm the entire scene is first transformed with a global transformation such as with a Fourier or Hadamard transform. The consequence of this transformation is that coherently linked structures within the scene, such as texture fields, condense into one, or a few, distinctive peaks. These peaks may then be selectively extracted (or rejected) by a variety of supplementary algorithms. The result is a modified coherent spectrum of the original scene. Through inverse transformation of this modified spectrum back to the image domain, the coherently linked structures are extracted. With this technique structures of related texture may be selectively, and globally, extracted even if they are not contiguous in the original image -and even in the presence of very substantial noise.

Paper Details

Date Published: 10 December 1986
PDF: 8 pages
Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); doi: 10.1117/12.976233
Show Author Affiliations
Chester L. Richards Jr., Technology Concepts Associates, Inc. (United States)

Published in SPIE Proceedings Vol. 0697:
Applications of Digital Image Processing IX
Andrew G. Tescher, Editor(s)

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