MATLAB-Based Face Classification Using AdaBoost Algorithm and JAFFE Database

A MATLAB implementation utilizing the AdaBoost algorithm for face classification, with the JAFFE facial database serving as the test dataset. The system identifies input faces by calculating similarity scores between the input image and all prototype faces in the database, then ranking the results to determine identity. Key implementation steps include: 1. Model Training: Click the [Train] button to build the recognition model using 15 face images per subject from JAFFE database 2. Test Image Selection: Click [Open] to select a face image from JAFFE for testing 3. Recognition: Click [Identify] to automatically classify the input face and display results