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Information 2017, 8(3), 97;

Review of Recent Type-2 Fuzzy Image Processing Applications

Calzada Tecnologico s/n, Tijuana Institute of Technology, 22379 Tijuana, Mexico
Universidad Autonoma de Baja California, Calzada Universidad #14418, Parque Industrial Internacional, 22390 Tijuana, Mexico
Author to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 5 August 2017 / Accepted: 8 August 2017 / Published: 10 August 2017
(This article belongs to the Special Issue Fuzzy Logic for Image Processing)
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This paper presents a literature review of applications using type-2 fuzzy systems in the area of image processing. Over the last years, there has been a significant increase in research on higher-order forms of fuzzy logic; in particular, the use of interval type-2 fuzzy sets and general type-2 fuzzy sets. The idea of making use of higher orders, or types, of fuzzy logic is to capture and represent uncertainty that is more complex. This paper is focused on image processing systems, which includes image segmentation, image filtering, image classification and edge detection. Various applications are presented where general type-2 fuzzy sets, interval type-2 fuzzy sets, and interval-value fuzzy sets are used; some are compared with the traditional type-1 fuzzy sets and others methodologies that exist in the literature for these areas in image processing. In all accounts, it is shown that type-2 fuzzy sets outperform both traditional image processing techniques as well as techniques using type-1 fuzzy sets, and provide the ability to handle uncertainty when the image is corrupted by noise. View Full-Text
Keywords: type-2 fuzzy sets; image processing; edge detection; image segmentation; image filtering; image classification type-2 fuzzy sets; image processing; edge detection; image segmentation; image filtering; image classification

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Castillo, O.; Sanchez, M.A.; Gonzalez, C.I.; Martinez, G.E. Review of Recent Type-2 Fuzzy Image Processing Applications. Information 2017, 8, 97.

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