An Application of Face Recognition System using Image Processing and Neural Networks

In recent years face recognition has receivedsubstantial attention from both research communities and themarket, but still remained very challenging in realapplications. A lot of face recognition algorithms, along withtheir medications, have been developed during the pastdecades. A number of typical algorithms are presented.In this paper, we propose to label a Self-Organizing Map(SOM) to measure image similarity. To manage this goal, wefeed Facial images associated to the regions of interest into theneural network. At the end of the learning step, each neuralunit is tuned to a particular Facial image prototype. Facialrecognition is then performed by a probabilistic decision rule.This scheme offers very promising results for faceidentification dealing with illumination variation and facialposes and expressions. This paper presents a novel Self-Organizing Map (SOM) for face recognition. The SOMmethod is trained on images from one database. The novelty ofthis work comes from the integration of A facial recognitionsystem is a computer application for automatically identifyingor verifying a person from a digital image or a video framefrom a video source. One of the way is to do this is bycomparing selected facial features from the image and a facialdatabase. It is typically used in security systems and can becompared to other biometrics such as fingerprint or eye irisrecognition systems.