Abstract
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.
Highlights
The definition of information is completely related to the definition of uncertainty [1,2]
If the problem to be treated has a high degree of uncertainty or it has uncertainty that is more complex, it is convenient to use interval type-2 fuzzy logic systems (IT2 FS) [4], or an interval-valued fuzzy set [3]; there are generalized type-2 fuzzy logic systems (GT2 FLS) which are capable of handling large amounts of uncertainty
In the results presented by the authors, the values achieved by the edge detection method based on IT2 FS after the optimization process using cuckoo search (CS) and genetic algorithms (GAs) were very similar; these optimizations improved the results achieved by the non-optimized IT2 FS
Summary
The definition of information is completely related to the definition of uncertainty [1,2]. We must mention that the selection of papers considered in this review has been performed by using the search engine available in the Scopus online system of Elsevier, where the papers can be searched for by author names or by subject In this sense, we must mention that a search for papers on T2 FLS on applications of image processing was done by using the following keywords: (“type-2 fuzzy” or “fuzzy type-2”) and (“processing” or “edge detection” or “segmentation” or “filter” or “morphology” or “smoothing” or “image” or “classification”). We must mention that a search for papers on T2 FLS on applications of image processing was done by using the following keywords: (“type-2 fuzzy” or “fuzzy type-2”) and (“processing” or “edge detection” or “segmentation” or “filter” or “morphology” or “smoothing” or “image” or “classification”) This resulted in 35 research papers found in various journals which were published from the year 2000 to 2017.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
