Review of recent type-2 fuzzy image processing applications

被引：45

作者：

Castillo, Oscar ^{[1
]}

Sanchez, Mauricio A. ^{[2
]}

Gonzalez, Claudia I. ^{[1
]}

Martinez, Gabriela E. ^{[1
]}

机构：

[1] Calzada Tecnologico s/n, Tijuana Institute of Technology, Tijuana,22379, Mexico

[2] Universidad Autonoma de Baja California, Calzada Universidad #14418, Parque Industrial Internacional, Tijuana,22390, Mexico

来源：

Information (Switzerland) | 2017年 / 8卷 / 03期

关键词：

Computer circuits - Image segmentation - Fuzzy sets - Image classification - Fuzzy logic;

D O I：

10.3390/info8030097

中图分类号：

学科分类号：

摘要：

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. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.

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