Distributed object recognition system

This paper presents the development of a real-time system for object recognition. In contrast to current approaches which mostly rely on specialized multiprocessor architectures for fast processing, we adopt a quite different approach using a distributed network architecture to support parallelism and attain real-time performance. Based on our previous work, this paper details a simple but effective and efficient matching approach to measure the degree of similarity between two image sets that are superimposed on one another. The novelty of our algorithm is to introduce some techniques used in distributed systems for the parallel implementation of a hierarchical image matching scheme. All of the implementation is on general-purpose message-passing architectures which are available on most of the existing computer systems. The system performance is evaluated in terms of recognition accuracy and execution time. Our investigation shows that distributed memory multicomputer can meet the high demand of computation and memory access in real-time imaging.