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Information 2017, 8(3), 104; doi:10.3390/info8030104

Edge Detection Method Based on General Type-2 Fuzzy Logic Applied to Color Images

Tijuana Institute of Technology, Tijuana 22379, Mexico
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Received: 1 July 2017 / Revised: 22 August 2017 / Accepted: 25 August 2017 / Published: 28 August 2017
(This article belongs to the Special Issue Fuzzy Logic for Image Processing)
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Abstract

This paper presents a new general type-2 fuzzy logic method for edge detection applied to color format images. The proposed algorithm combines the methodology based on the image gradients and general type-2 fuzzy logic theory to provide a powerful edge detection method. General type-2 fuzzy inference systems are approximated using the α-planes approach. The edge detection method is tested on a database of color images with the idea of illustrating the advantage of applying the fuzzy edge detection approach on color images against grayscale format images, and also when the images are corrupted by noise. This paper compares the proposed method based on general type-2 fuzzy logic with other edge detection algorithms, such as ones based on type-1 and interval type-2 fuzzy systems. Simulation results show that edge detection based on a general type-2 fuzzy system outperforms the other methods because of its ability to handle the intrinsic uncertainty in this problem. View Full-Text
Keywords: α-planes; general type-2 fuzzy sets; general type-2 fuzzy sets; interval type-2 fuzzy sets; type-1 fuzzy sets; image processing; color edge detection; computer vision α-planes; general type-2 fuzzy sets; general type-2 fuzzy sets; interval type-2 fuzzy sets; type-1 fuzzy sets; image processing; color edge detection; computer vision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Gonzalez, C.I.; Melin, P.; Castillo, O. Edge Detection Method Based on General Type-2 Fuzzy Logic Applied to Color Images. Information 2017, 8, 104.

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