A-IFSs entropy based image multi-thresholding

Authors:
Pedro Couto;Humberto Bustince;Miguel Pagola;Aranzazu Jurio;Pedro Melo-Pinto
Affiliations:
CITAB, UTAD University, Vila Real, Portugal;UPNA, Dept. de Automática y Computación, Pamplona, Spain;UPNA, Dept. de Automática y Computación, Pamplona, Spain;UPNA, Dept. de Automática y Computación, Pamplona, Spain;CITAB, UTAD University, Vila Real, Portugal
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

Citing 5
Cited 0

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Abstract

In this work, a computationally efficient segmentation framework is proposed. The proposed methodology is able to auto determine the optimal number of required thresholds in order to achieve a good and accurate segmentation. Atanassov's intuitionistic fuzzy sets and intuitionistic fuzzy entropy in particular, play an important role in the determination of both the threshold value and the number of required thresholds. Experimental results and their evaluation according to uniformity measures are presented.