A Survey on Data Mining Classifiers for Face Verification
Amina K1, Lekshmy P L2
1Amina K, M.Tech. Scholar, Deparftment of Computer Science and Engineering, LBS Institute of Technology for Women, Poojappura, Trivandrum (Kerala), India.
2Lekshmy P L, Assistant Professor, Deparftment of Computer Science and Engineering, LBS Institute of Technology for Women, Poojappura, Trivandrum (Kerala), India.
Manuscript received on 13 June 2016 | Revised Manuscript received on 20 June 2016 | Manuscript Published on 30 June 2016 | PP: 177-179 | Volume-5 Issue-5, June 2016 | Retrieval Number: E4647065516/16©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now a days the human face plays an important role in our social interaction, conveying peoples identity. Face recognition is a rapidly growing field today for many uses in the fields of biometric authentication, security and many other areas. An automatic face recognition system will find many applications such as human computer interface, model based video coding and security control systems. Face Recognition System is a computer application for automatically identifying or verifying a person from a digital image or a single frame from a video source. This can be done by comparing selected facial characteristics of the likeness and a facial database. The difficulties of face recognition arising from face characteristics, geometry, image quality and image content. In this paper there are different data mining classifiers are used for face verification. Also we shall see their advantages, disadvantages and solutions to overcome the problems.
Keywords: Face Recognition System, Support Vector Machine (SVM), Discriminative Multi-Projection Vectors (DMPV), Gaussian Mixture Model (GMM).
Scope of the Article: Data Mining