Recursive algorithm based on fuzzy 2-partition entropy for 2-level image thresholding

Authors:
Souad Benabdelkader;Mohammed Boulemden
Affiliations:
Department of Electronics, University of Batna, Rue Chahid Boukhlouf Med El-Hadi, Batna 05000, Algeria;Department of Electronics, University of Batna, Rue Chahid Boukhlouf Med El-Hadi, Batna 05000, Algeria
Venue:
Pattern Recognition
Year:
2005

Citing 2
Cited 1

A survey of thresholding techniques

Computer Vision, Graphics, and Image Processing
Goal-Directed Evaluation of Binarization Methods

IEEE Transactions on Pattern Analysis and Machine Intelligence

A fast recursive algorithm based on fuzzy 2-partition entropy approach for threshold selection

Neurocomputing

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Abstract

The fuzzy c-partition entropy approach for threshold selection behaves well in segmenting images. But the size of search space increases very rapidly when the number of parameters needed to determine the membership function increases. The computation complexity of the fuzzy 2-partition entropy approach is bounded by O(L^3). In this paper, a recursive scheme which decreases the computation complexity of the basic algorithm to O(L^2) is proposed. The approach does not need the calculation of the membership function. The processing time of each image is reduced from more than 5min to less than 20s.