Paper
10 December 1986 A New Image Segmentation And Texture Analysis Algorithm
Chester L. Richards Jr.
Author Affiliations +
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.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chester L. Richards Jr. "A New Image Segmentation And Texture Analysis Algorithm", Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); https://doi.org/10.1117/12.976233
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KEYWORDS
Image filtering

Image segmentation

Optical filters

Image processing algorithms and systems

Coherence (optics)

Nonlinear filtering

Diffusion

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