Classification of Eyes Based on Fuzzy Logic

Mohamed Fakir, Hatimi Hicham, Mohamed Chabi and Muhammad Sarfraz
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Mohamed Fakir: Faculty of Sciences and Technics, Beni Mellal, Morocco
Hatimi Hicham: Sultan Moulay Slimane University, Morocco
Mohamed Chabi: Faculty of Sciences and Technics, Beni Mellal, Morocco
Muhammad Sarfraz: Kuwait University, Kuwait

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2020, vol. 14, issue 4, 101-112

Abstract: The systems of eye classification in an image are indispensable in several domains. To better find the class of membership of the eye in a minimal time, the classic methods of detection are inadequate. Fuzzy logic is considered to be an effective technique for solving an eye classification problem. This article proposes a fuzzy approach for eye classification. The tasks of classification are realized in two steps. In the first step, the characteristic points of the image are extracted in order to locate the eye. These characteristic points allow generating a representative model of the eye. In the second step, the detected eyes have to pass by a fuzzy controller containing several parts: Fuzzification, inference rules, and defuzzification. Finally, the system gives the degree of membership of the detected eyes to each class in the database.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jcini0:v:14:y:2020:i:4:p:101-112

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