This is a classroom attendance system using MATLAB that uses both facial recognition and fingerprint to enter the classroom.
The algorithm used for the face recognition is PCA. Principal component analysis is one of the most effective face recognition techniques, which converts a correlated training set of variables into principal mode of variation through following orthogonal transformation procedure. Primarily PCA reduces definition requirement of an image by analyzing the principal components (feature extraction). The feature extraction may not incorporate much physical details, as they mostly include statistical characteristics.
The algorithm used for fingerprint recognition in this project is minutiae matching by scoring. Minutiae is the collection of ridges ending and ridge bifurcation features of a fingerprint. Ridges exclusively defines uniqueness of a fingerprint through their characteristics and relationship with neighboring ridges.
System Architecture
