Bank Locker Security System Using Machine Learning with Face and Liveness Detection

Abstract: In this Paper we implemented and design Face recognition play a vital role in variety of applications from biometrics, surveillance, security, identification to the authentication. In this paper we design and implement a Bank locker security system where access people whose faces are available in the training database. First, we are going to detect the face by detecting the human motion. Then face recognition is performed to determine the authority of the person to enter the sensitive area. At the same time, we track the coordinate of detected motion. Failing to recognize the face finally passes the estimated coordinate to anesthetic gun for targeting the intruder automatically. Experimental results demonstrate the effectiveness of proposed Bank locker security system in order to restrict the unauthorized access and enhanced reliability by use of Liveness face recognition.

Keywords: Face Detection, Feature Extraction, Tracking, Machine Learning.