Authentic Gate Entry System (AuthGES) by Using LBPH for Smart Home Security

Abstract

In this paper, a smart home security system by using local binary pattern histograms (LBPH) face detection algorithm is proposed to enhance the security level of entry-system. Face recognition is an interesting but challenging in machine learning field and impacts important applications in many areas such as remote sensing, machine/robot vision, pattern recognition, medical field, banking and security system access, and authentication in personal electronics gadget. In this research paper, we proposed the door lock security system using image processing instead of traditional key and digital lock system. The image processing mainly consists of three parts, namely face representation, feature extraction and identification of face. Face representation represents how to model a face with LBPH algorithms of detection and recognition. The most useful and unique features of the face image are extracted in the feature extraction phase. In the identification of face the new face image is compared with the images which are already extracted and saved on database. Face detection and recognition method was applied to allow the authorized dwellers and the guest and prevent unwanted person to enter inside the house.