Implementation of Haar Cascade classifier method and local binary pattern histogram on face identification.

The face is one part of the human body that is unique and has a characteristic to be easily recognized. Face detection, facial recognition, facial expression analysis, and facial demographic classification are the subsets of computer vision and image processing that have received much attention in recent decades. The purpose of this study is to implement the Haar Cascade Classifier and Local Binary Pattern methods on the face recognition system and to determine the performance of the Haar Cascade Classifier and Local Binary Pattern Histogram methods in recognizing faces in images that have one look. The technique used in this research is Haar Cascade Classifier as a face detection method and the Local Binary Pattern Histogram method for face recognition. In this study, the development of a facial recognition system uses the Python programming language with the help of the OpenCV library. Based on the test results, the accuracy of the face recognition system with bright and dim lighting conditions is 88% and 70%, respectively. The accuracy of all test results is 79%. [ABSTRACT FROM AUTHOR]