Real Time Human Face Detection and Recognition Based on Haar Features

In this research, a system has been designed which is based on the approach to measure the effectiveness of different feature types. There are eight different Haar features. This work has considered only six of them. The implemented system has been trained by using a handpicked database. Additionally, Variable illumination condition and occlusion on the face are one of the biggest hinders of facial data processing. Therefore, a database has been built by considering these factors. This research contains sample images from various persons with various poses, and lighting condition etc. The detectors that have been used in this work which has been trained by using numerous stages of classifying such as weak classifier and strong classifier. If the image can pass through all stages of the detector, then the face will be recognized. After identifying, it will compare locally stored database for comparison. If it matches with the database, then the face will be detected automatically and the real-time output will be shown.