2D-DCT Distance Based Face Recognition Using a Reduced Number of Coefficients

Automatic face recognition is a challenging problem, since human faces have a complex pattern. This paper presents a technique for recognition of frontal human faces on gray scale images. In this technique, the distance between the Discrete Cosine Transform (DCT) of the face under evaluation and all the DCTs of the faces database are computed. The faces with the shortest distances probably belong to the same person; therefore this evaluating face is attributed to this person. The distance is calculated as the sum of the differences between the modules of DCT coefficients. Only a few coefficients are used in this computation; they are selected from the low frequency of the DCT. Experimental tests on the ORL database reaches a recognition rate of 99.75%, with low computational cost and no preprocessing step. Additionally, the method achieved 100.0% of recognition accuracy when applying a zooming normalization over the ORL database.