A Fuzzy Clustering Approach for Face Recognition Based on Face Feature Lines and Eigenvectors

A Fuzzy Clustering Approach for Face Recognition Based on Face Feature Lines and Eigenvectors
By Pablo Rivas Perea

Abstract— This paper presents a new approach aimed to design a fuzzy face recognition system. Face feature lines, new features proposed in the paper, are incorporated in the feature vector used to design the patter recognition system. Face feature lines are considered as new features based on previous studies related to
face recognition tasks on newborns. Besides the face feature lines the feature vector incorporates eigenvectors of the face image obtained with the Karhunen-Loeve transformation. The fuzzy face recognition system is based on the Gath-Gheva fuzzy clustering method and the Abonyi and Szeifert classification scheme. The performance of the face recognition system turned out to be 90% of correct classification tested on the ORL and Yale databases.

Index Terms—Face Recognition, Face Feature Lines, Fuzzy
Clustering.

Published for the Journal: Engineering Letters, 15:1, EL_15_1_6

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