Fuzzy Face Recognition Based On Skin Texture Fusion Model

Abstract

Facerecognition is a research are in computer vision and pattern recognition because of its importance in real applications like human machine interaction, video surveillance, and security systems. Here we have proposed a fuzzy model for robust facerecognition using gradient and texture information. Initially, the local binary pattern (LBP) and histogram of oriented gradients (HOG) feature of face skin from the original images are extracted. These two features are used for the development of our fuzzy model. For the analysis of faces, a content-based similarity measure is developed and used for data analysis of trained face model and test face model. The proposed algorithm is experimented on LFW, AR, and ORL face databases. The proposed fuzzy face fusion model approach shows that our proposed method is having good recognition rate compared to facerecognition methods developed recently.