Human Identification System based on Face using Active Horizontal Levels (AHLs) Feature

Nowadays, face is a crucial field for many pattern recognition researchers. It is considered as a good way for biometric authentication in many surveillance systems. The most important issue in face recognition is the features extraction from the face's images of the person's images or videos. In this paper, a proposed method has been introduced to identify person images, which are captured by cameras. This method depends on Active Horizontal Levels (AHLs) feature. Gain ratio attribute (feature) selection has been used to choose the Horizontal Levels (HLs) that lead to the highest identification rate. The proposed method was evaluated against BioID, UK, ORL and FEI face database, to recognize person from one image. The experimental results reveal the effectiveness of our proposed method against other face recognition methods to achieve better accuracies.