An Approach for Fast Face Image Matching Based on Self-adaption Grid Division and Its Vector Coding
基于自适应网格矢量编码的人脸快速匹配算法

Face recognition is a new research topic in today's pattern recognition field.With analyzing the advantages and disadvantages of transient image matching algorithm,a new algorithm for fast human face image matching based on self-adaption grid division and vector coding is presented in this paper.On the premise of the edge extraction and two-value characterization,and face contour extraction,the two images' edges are firstly divided into several grids, and then the segments of the edges and character contour within each grid are described with chain and vector coding.Finally,by computing the similarities and shape alteration between the vector codes,the course of goal matching and recognition is accomplished.The simulative experiment is carried out on the standard ORL face database.Satisfied results have been obtained,which show that the proposed algorithm can not only effectively resolve the problems caused by lower recognition owing to image rotation,minute alteration of edge shape caused by pose transformation and different illumination condition,but also greatly enhance the matching precision and reduce the redundant information and the complexity of computation.