Neural Network Retinal Model Real Time Implementation

The solution of complex image processing problems, both military and commercial are expected to benefit significantly from research onto biological vision systems. However, current development of biological models of vision are hampered by lack of low-cost, high-performance, computing hardware that addresses the specific needs of vision processing. The goal of this SBIR Phase I project has been to take a significant neural network vision application and to map it onto dedicated hardware for real time implementation. The neural network was already demonstrated using software simulation on a general purpose computer. During Phase 1, HNC took a neural network model of the retina and, using HNC's Vision Processor (ViP) prototype hardware, achieved a speedup factor of 200 over the retina algorithm executed on the Sun SPARCstation. A performance enhancement of this magnitude on a very general model demonstrates that the door is open to a new generation of vision research and applications. The model is described along with the digital hardware implementation of the algorithm using the new ViP chip set.