Journal
APPLIED SOFT COMPUTING
Volume 47, Issue -, Pages 631-643Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2014.12.010
Keywords
Interval type-2 fuzzy logic; Edge detection; Image processing; Cuckoo Search algorithms
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Funding
- CONACYT [44524, 178539]
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This paper presents the optimization of a fuzzy edge detector based on the traditional Sobel technique combined with interval type-2 fuzzy logic. The goal of using interval type-2 fuzzy logic in edge detection methods is to provide them with the ability to handle uncertainty in processing real world images. However, the optimal design of fuzzy systems is a difficult task and for this reason the use of meta heuristic optimization techniques is also considered in this paper. For the optimization of the fuzzy inference systems, the Cuckoo Search (CS) and Genetic Algorithms (GAs) are applied. Simulation results show that using an optimal interval type-2 fuzzy system in conjunction with the Sobel technique provides a powerful edge detection method that outperforms its type-1 counterparts and the pure original Sobel technique. (C) 2014 Elsevier B.V. All rights reserved.
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