Multi-Faces Recognition Process Using Haar Cascades and Eigenface Methods

Abstract

Face recognition can be considered one of the most successful biometric identification methods among several types of biometric identification including fingerprints, DNA, palm print, hand geometry, iris recognition, retina and odour/scent. Face recognition provides biometric identification that utilizes the uniqueness of faces for security purposes. The problem with face recognition using biometric identification is its lengthy process and the accuracy of the results. This paper proposes solutions for a faster face recognition process with accurate results. The proposed face recognition process was done using a hybrid process of Haar Cascades and Eigenface methods, which can detect multiple faces (55 faces) in a single detection process. This improved face recognition approach was able to recognize multiple faces with 91.67% accuracy level.