Efficient Image-Vector-Generation Processor for Edge-Based Complementary Feature Representations

Abstract

A digital processor dedicated to edge-based image vector generation has been developed aiming at real-time image recognition. The processor consists of an on-chip memory and 16 single instruction multiple data (SIMD) processing elements. The capacity of the on-chip memory as well as the overhead for starting the processing have been minimized by introducing a seamless data transferring scheme from memory to processing elements. The 16 SIMD processing elements work together either as accumulators or as shift registers, thus achieving a very efficient generation of two different kinds of feature vector: projected principal-edge distribution (PPED)[3,4] and averaged principal-edge distribution (APED).[5] Concurrent use of these two vectors is shown to be very important for robust image recognition.[5] The chip was fabricated using 0.18-µm complementary metal oxide semiconductor (CMOS) technology and the generation of 64-dimension PPED and APED vectors at 84.7 and 83.9 fps, respectively, from video graphics array (VGA) size images was demonstrated at 62.5 MHz.