Face and eye detection by CNN algorithms

A novel approach to critical parts of face detection problems is given, bas ed on analogic cellular neural network (CNN) algorithms. The proposed CNN a lgorithms find and help to normalize human faces effectively while their ti me requirement is a fraction of the previously used methods. The algorithm starts with the detection of heads on color pictures using deviations in co lor and structure of the human face and that of the background. By normaliz ing the distance and position of the reference points, all faces should be transformed into the same size and position. For normalization, eyes serve as points of reference. Other CNN algorithm finds the eyes on any grayscale image by searching characteristic features of the eyes and eye sockets. Te sts made on a standard database show that the algorithm works very fast and it is reliable.