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Proceedings Paper

Fuzzy logic image-clustering algorithm
Author(s): Rustom Mamlook; Wiley E. Thompson
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Paper Abstract

A fuzzy logic clustering algorithm to classify a given image into targets and backgrounds is presented. The algorithm forms clusters and is trained without supervision. The clustering is done on the basis of the statistical properties of the set of inputs. The algorithm features an adaptive mechanism for selecting the number of clusters, and it features an adaptive threshold. The problem of threshold selection is considered and the convergence of the algorithm is shown. The algorithm also does not require the number of clusters been known a priori. An example is given to illustrate the application of the algorithm.

Paper Details

Date Published: 28 July 1997
PDF: 7 pages
Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); doi: 10.1117/12.280837
Show Author Affiliations
Rustom Mamlook, Applied Science Univ. (Jordan)
Wiley E. Thompson, New Mexico State Univ. (United States)


Published in SPIE Proceedings Vol. 3068:
Signal Processing, Sensor Fusion, and Target Recognition VI
Ivan Kadar, Editor(s)

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