A Resultant of Local Binary Pattern Histogram (LBPH) and Speeded Up Robust Feature (SURF) Algorithm for Face Recognition

In the time of increasing crime Face recognition is very significant with regards to computer vision, security, monitoring, reconnaissance, pattern checking, neural network, realtime video processing, etc. Face is non- interfering solid Biometrics for distinguishing people and subsequently goons consistently attempt to cover their faces by various fake methods, for example, plastic surgery, mask, etc. The accessibility of an exhaustive face database is vital to test the working of these algorithms of face recognition. Though, we-tested freely accessible face databases as well as self-created one containing face pictures with a wide assortment of postures, light, signals and face impediments. The contribution of this research paper is Comparing Local Binary Pattern Histogram (LBPH) and Speeded Up Robust Feature (SURF) algorithms and finding the best among them.