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Summary
In this study, a facial recognition login system for websites and applications was developed were Machine Learning classifier algorithm was used to detect and recognize images of the system users. The study focused on designing and implementing a face recognition system. The System is composed of image acquisition, face detection part, face recognition part, and identification of person user and login system. Fast Forward Neural Network (FFNN) and Rocal Binary Pattern Histogram (LBPH) is employed to classify and to solve pattern recongition problem since face recognition is a kind of pattern recognition. Classification result is accurate. Classification is also flexible and correct when extracted face image is small oriented, closed eye, and small smiled. Proposed algorithm is capable of detect multiple faces, and performance of system has acceptable good results. Proposed system can be affected by pose, presence or absence of structural components, facial expression, imaging condition, and strong illumination
