Fuzzy matching of edge and curvature based features from range images for 3D face recognition

Abstract

AbstractAutomatic human face recognition is already in research from some decades due to its application in different fields. But there is no unique technique that is very much worthwhile for robust automatic human face recognition, suitable for all possible situations. In this paper, a new technique is proposed, which is a holistic approach, and it is based on ‘one to all’ comparison method. Along with the edge, four different types of curvatures are computed from face image profile to capture both the local features and surface features from 3D face image. Then, a new feature space, EC (Edge_Curvature) image, is generated for feature estimation during final recognition purpose. The similarities among intra-class members are carried out using fuzzy rule derived from the computed distance vectors by Hausdorff, distance that is used to match the probe images for the classification purpose automatically. For the validation of the algorithm, the algorithm is experimented on Frav3D and GavabDB databases with ...