An associative processing module for a heterogeneous vision architecture

Abstract

The heterogeneous vision architecture that satisfies the computing demands of real-time computer vision by providing parallelism in three different forms is described. A pipeline of digital signal processing (DSP) chips initially processes signals. Then a SIMD associative processor array processes images and extract features, and a MIMD network of transputers processes extracted objects in parallel. The array's VLSI implementation, the processing modes available due to the use of content-addressable memory, and the means of achieving efficient 2-D interprocessor communication in the linear array are described. An application as a vehicle number plate recognition system is presented. >