Biology-inspired early vision system for a spike processing neurocomputer

Abstract

Examinations of the early vision system of mammals have shown Gabor-like behaviour of the simple cell responses. Furthermore, the advantages of sc Gab or-like image filtering are evident in computer vision. This causes strong demand to achieve Gabor-like responses in biology inspired spiking neural networks and so we propose a neural vision network based on spiking neurons with Gabor-like simple cell responses. The Gabor behaviour is theoretically derived and demonstrated with simulation results. Our network consists of a cascaded structure of photoreceptors, ganglion and horizontal neurons and simple cells. The receptors are arranged on a hexagonal grid. One main advantage of our approach compared to direct Gabor filtering is the availability of valuable intersignals. The network is designed as the preprocessing stage for pulse-coupled neural vision networks simulated on the SPIKE neurocomputer architecture. Hence, the simple cells are implemented as Eckhorn neurons.