Automatic face recognition has been a difficult problem in the field of computer vision for many years. Robust face recognition requires the ability to recognize identity despite many variations in appearance the face can have in a scene.
A major advantage of using biometric products, therefore, is that you can identify yourself and gain access to secure systems without having to carry a key or remember a password or PIN number.
Due to the recent advances in visual communication and face recognition technologies, automatic face recognition has attracted a great deal of research interest. Being a diverse problem, the development of face recognition research has comprised contribution of researchers from various fields of sciences.
We propose preceding recognition with a feature based algorithm capable of searching images for human faces efficiently and pre-processed image previously for better manipulation results.
The facial contour is estimated by computing symmetric enclosure and is used to guide the search for feature points within the face. Localization of face features like the eyes, mouth and nose of each individual is done. The resulting description is matched against a database using simple distance measures to determine the face’s identity as one of the previously identified training examples.