Human face recognition project - Bartolome, Janice M. (2002)
The Human Face Recognition in Images Project is designed to recognize scanned facial images. Given an input image in RGB format, it can recognize the person, that is, it identifies whether the person is in the current database or not. The project is divided into two major parts: face segmentation and face recognition. The facial feature of the image is extracted from the background using the codebook generated by the Linear Vector Quantization (LVQ) algorithm. The segmented image is then converted into its grayscale format as input to the next module. The Back Propagation algorithm is responsible for the recognition part. The Human Face Recognition in Images Project is able to recognize up to 83% accuracy level.