A novel approach to design a massively parallel application specific architecture for image recognition systems

Abstract

The goal of the paper is to present a novel approach for designing massively parallel architectures for image recognition systems. Massive parallel hardware produces high speed image recognition. Hardware architectures work much faster and are more effective for application specific processing than a software-based image recognition system. The concept of designing optimal image recognition systems with high speed, low complexity, good portability, and low cost has been present for a long time. The authors have considered the basic design factors, simple and regular design, concurrency and communication, and balancing computation with I/O. The technique presented provides a new method of designing an image recognition system by concentrating on modularity and massive parallelism. This is accomplished through the design of a processing element layer, local communicator layer, and network of new image layer. The processing element (PE) layer performs the basic recognition functions on individual pixels through logical operations. Both the local communicator and network of new image layers institute a mesh network topology, which has proven to be the fastest and most efficient. The local communicator layer has the most important function, it communicates with the other two layers, combines results from the PE layer, and houses the main control unit. All layers work simultaneously, or in other words, in a parallel fashion. The flow diagram of a CAD designer algorithm, based on this new design technique, is presented.