Comparison of face Recognition Algorithms on Dummy Faces

In the age of rising crime face recognition is enormously important in the contexts of computer vision, psychology, surveillance, fraud detection, pattern recognition, neural network, content based video processing, etc. Face is a non intrusive strong biometrics for identification and hence criminals always try to hide their facial organs by different artificial means such as plastic surgery, disguise and dummy. The availability of a comprehensive face database is crucial to test the performance of these face recognition algorithms. However, while existing publicly-available face databases contain face images with a wide variety of poses, illumination, gestures and face occlusions but there is no dummy face database is available in public domain. The contributions of this research paper are: i) Preparation of dummy face database of 110 subjects ii) Comparison of some texture based, feature based and holistic face recognition algorithms on that dummy face database, iii) Critical analysis of these types of algorithms on dummy face database.