3D Face Recognition in Biometrics

-Biometrics is the area of bioengineering that pursues the characterization of individuals in a population (e.g., a particular person) by means of something that the individual is or produces. Among the different modalities in biometrics, face recognition has been a focus in research for the last couple of decades because of its wide potential applications and its importance to meet the security needs of today’s world. Most of the systems developed are based on 2D face recognition technology, which uses pictures for data processing. With the development of 3D imaging technology, 3D face recognition emerges as an alternative to overcome the difficulties inherent to 2D face recognition, i.e. sensitivity to illumination conditions and positions of a subject. But 3D face recognition still needs to tackle the problem of deformation of facial geometry that results from the expression changes of a subject. To deal with this issue, a 3D face recognition framework is proposed in this paper. It is composed of three subsystems: expression recognition system, expressional face recognition system and neutral face recognition system. A system for the recognition of faces with one type of expression (smile) and neutral faces was implemented and tested on a database of 30 subjects. The results proved the feasibility of this framework. Key-Words: face recognition, biometrics, 2D, 3D, range image, PCA, subspace, SVM, LDA