Description

Face recognition which is a combination of machine learning and the biometric techniques which holds the qualities of not only high precision but also the reliability. The proposed system consists of different steps, including training of images, face detection using Haar-classifier, comparison of trained images, result based on the comparison. An important application of interest is automated surveillance, where the objective is to recognize people who are on a watch list. Haar cascading is one of the algorithm for face detection. Here we use Haar like classifiers to track faces on OpenCV platform. The system is identified the person is crime or normal. If the person is crime, the details will be shown. The system is developed the different classification algorithm such as random forest and CNN. Finally, the experimental results shows that some performance metrics such as accuracy and error rate.