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Proceedings Paper

Fuzzy Segmentation Of Natural Scenes Using Fractal Geometry
Author(s): James M. Keller; Thomas Downey
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Paper Abstract

Segmentation of an image into meaningful regions is a crucial component in intelligent scene understanding. In images of natural scenes there is a high degree of variability and uncertainty in the features which represent the regions and objects. In previous papers, new features, based on fractal geometry, were introduced to describe natural textured regions. In this paper, those fractal features are utilized as descriptors in segmentation algorithms which produce fuzzy partitions of the image plane. In particular, segmentation schemes based on the fuzzy K-nearest-neighbors and split-and-merge are implemented to segment digital images.

Paper Details

Date Published: 27 March 1989
PDF: 8 pages
Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); doi: 10.1117/12.960297
Show Author Affiliations
James M. Keller, University of Missouri-Columbia (United States)
Thomas Downey, University of Missouri-Columbia (United States)


Published in SPIE Proceedings Vol. 1002:
Intelligent Robots and Computer Vision VII
David P. Casasent, Editor(s)

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