Study of the contrast processing in the early visual system using a neuromorphic retinal architecture
In this paper we propose a retinal architecture that incorporates the neural circuits found in the different retinal regions. It is implemented in a reconfigurable system for observing in real time the contrast processing capabilities of each retinal region over the provided stimuli. The retina model is based on a discrete-time cellular neural network (DTCNN) that will be implemented on reconfigurable architecture (FPGA) with a time multiplexing approach. This architecture is able to incorporate 50 million neurons in its structure for processing video in real time. It has been observed that the contrast detection and the detail resolution are influenced by the convergence factor of neurons and by the lateral inhibition, specific characteristics of each neural circuit.
cellular neural network retinal contrast processing retinomorphic systems reconfigurable computing