Classification of Eyes Based on Fuzzy Logic

Muhammad Sarfraz, Mohamed Fakir, Hatimi Hicham, Mohamed Chabi

OAI: oai:igi-global.com:261775 • DOI: 10.4018/IJCINI.2020100106

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.

Cognitive Informatics Computer Science and Information Technology Cognitive Informatics