抄録
As one of human like foveation systems, we present the autonomous foveating system based on the Pulse-Coupled Neural Network(PCNN). The PCNN is expected to be useful for the image processing. This system spontaneously selects the foveation points from the edges and/or optical flows of the input images through the PCNN without any training. The foveation point is defined as the point with the maximum output from the PCNN. The output of the original PCNN neuron takes binary value, so the PCNN would select a lot of candidates for the foveation points. To avoid such confusing situation, we adopt the sigmoidal pulse generator. This decreases the candidates for the foveation points to a few or a single candidate. It is also given some experiments to show the effectiveness of the autonomous foveating system through the PCNN.
