Face recognition based on face partitions using Common Vector Approach

In this study, the four different partitions (right eye, left eye, nose and mouth) that include more important information than other parts in a face are cropped in order to overcome the large sample size problem for face recognition. The feature vectors of images of each individual are constructed from these four partitions and applied to Common Vector Approach (CVA) for the recognition purpose. The reasonable results imply that the feature vectors obtained from four partitions of faces can be efficiently used instead of the feature vectors constructed from whole face.