Abstract: “This paper introduces a new trend for face recognition features. It is based on dividing the face into four horizontal and five vertical regions [16]. Each region is divided into an optimum number of eight vertical and seven horizontal partitions. One approach using average per partition features and another using histogram per region features are considered. Algorithms to find the minimum of Euclidean distance (ED) between a test image and a matching DB registered image are discussed. Both algorithms achieved 100% recognition rate (RR) with ORL and Yale databases. A new definition for RR that is termed inclusive recognition rate (RRi) is suggested. RRi supports testing images belonging to DB subject's images or not.”

Keywords: Face features, Face partitions, Face recognition, Face regions, Image identification