Compensating for variable recording conditions in frontal face authentication algorithms
This paper addresses the problem of compensating for variable recording conditions such as changes in illumination, scale differences, and varying face position. It is well known that the performance of any face authentication/recognition algorithm deteriorates significantly in the presence of the aforementioned conditions as well as the expression variations. The use of simple and powerful pre-processing techniques aiming at compensating for variable recording conditions prior to the application of any authentication algorithm is proposed. It is shown that such an approach overcomes indeed the image variations and guarantees an almost stable performance for the Morphological Dynamic Link Architecture developed within the European research project M2VTS.