AER image filtering architecture for vision-processing systems

Abstract

A VLSI architecture is proposed for the realization of real-time two-dimensional (2-D) image filtering in an address-event-representation (AER) vision system. The architecture is capable of implementing any convolutional kernel F(x,y) as long as it is decomposable into x-axis and y-axis components, i.e., F(x, y) = H(x)V(y), for some rotated coordinate system {x, y} and if this product can be approximated safely by a signed minimum operation. The proposed architecture is intended to be used in a complete vision system, known as the boundary contour system and feature contour system (BCS-FCS) vision model, proposed by Grossberg and collaborators. The present paper proposes the architecture, provides a circuit implementation using MOS transistors operated in weak inversion, and shows behavioral simulation results at the system level operation and some electrical simulations.