Classification of Eyes Based on Fuzzy Logic

Classification of Eyes Based on Fuzzy Logic

Mohamed Fakir, Hatimi Hicham, Mohamed Chabi, Muhammad Sarfraz
Copyright: © 2020 |Pages: 12
DOI: 10.4018/IJCINI.2020100106
Article PDF Download
Open access articles are freely available for download

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.
Article Preview
Top

Research Method

The fuzzy system created in this paper allows giving the degree of membership of each eye located on an input image to the classes of the eyes recorded in a database (Figure 1):

Figure 1.

Steps of detection used in the fuzzy controller

IJCINI.2020100106.f01

Complete Article List

Search this Journal:
Reset
Volume 18: 1 Issue (2024)
Volume 17: 1 Issue (2023)
Volume 16: 1 Issue (2022)
Volume 15: 4 Issues (2021)
Volume 14: 4 Issues (2020)
Volume 13: 4 Issues (2019)
Volume 12: 4 Issues (2018)
Volume 11: 4 Issues (2017)
Volume 10: 4 Issues (2016)
Volume 9: 4 Issues (2015)
Volume 8: 4 Issues (2014)
Volume 7: 4 Issues (2013)
Volume 6: 4 Issues (2012)
Volume 5: 4 Issues (2011)
Volume 4: 4 Issues (2010)
Volume 3: 4 Issues (2009)
Volume 2: 4 Issues (2008)
Volume 1: 4 Issues (2007)
View Complete Journal Contents Listing