MATLAB Face Recognition Program with Haar Features and Adaboost Algorithm

This MATLAB-based face recognition program utilizes Haar-like features and the Adaboost algorithm for effective facial detection and identification. Face recognition represents a computer vision technique that detects and identifies human faces through image analysis. By examining patterns and features within digital images, the program can determine the presence of human faces and precisely locate facial regions with distinctive characteristics. The implementation employs Haar-like features, which are digital image features used for detecting edges, lines, and other visual patterns essential for object recognition. In MATLAB, these features are typically computed using integral images for efficient calculation through functions like integralImage() and haarFeatureExtract(). The rectangular features are evaluated at multiple scales and positions across the image using sliding window techniques. The Adaboost (Adaptive Boosting) algorithm serves as the machine learning component that enhances classifier accuracy by combining multiple weak classifiers into a strong classifier. The MATLAB implementation involves training stages where adaboostTrain() function sequentially selects the most discriminative Haar features and assigns appropriate weights to create a cascaded classifier structure. This cascade approach, implemented through vision.CascadeObjectDetector, allows for rapid rejection of non-face regions while concentrating computation on promising facial candidates. By integrating these two methodologies, the MATLAB face recognition program achieves efficient and accurate face detection capabilities. The program structure typically includes image preprocessing functions like imread() and rgb2gray(), feature extraction modules, classifier training routines, and real-time detection components using webcam() or videoReader() objects. This implementation provides researchers and developers with a powerful tool for advancing face recognition technology and its practical applications in security systems, biometric authentication, and human-computer interaction.