Automatic selection of object enhancement operator with quantitative justification based on fuzzy set theoretic measures

Kundu, Malay K. ; Pal, Sankar K. (1990) Automatic selection of object enhancement operator with quantitative justification based on fuzzy set theoretic measures Pattern Recognition Letters, 11 (12). pp. 811-829. ISSN 0167-8655

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Official URL: http://linkinghub.elsevier.com/retrieve/pii/016786...

Related URL: http://dx.doi.org/10.1016/0167-8655(90)90035-Z

Abstract

An algorithm for automatic selection of a nonlinear function appropriate for object enhancement of a given image is described. The algorithm does not need iterative visual interaction and prior knowledge of image statistics in order to select the transformation function for its optimal enhancement. A quantitative measure for evaluating enhancement equality has been provided based on fuzzy geometry. The concept of minimizing fuzziness (ambiguity) in both grayness and in spatial domain, as used by Pal and Rosenfeld [4], has been adopted. The selection criteria are further justified from the point of bounds of the membership function. The effectiveness of the algorithm is demonstrated for unimodal and right skewed images when possible nonlinear transformation functions are taken into account.

Item Type:Article
Source:Copyright of this article belongs to International Association for Pattern Recognition.
Keywords:Fuzzy Geometry; Object Enhancement; Grayness Amgibuity; Bounds
ID Code:26090
Deposited On:06 Dec 2010 13:07
Last Modified:13 Jun 2011 06:06

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