An alternative method for designing parallel image recognition systems: a feasibility study

The most successful image recognition systems have been developed in software. This method has proved to be quite laborious and the execution time is intensive. An alternative method of designing image recognition systems is needed. The goal is to design a reliable, compact, high speed, low cost recognition system. One way to reach this goal is to design the image recognition system via a massively parallel hardware architecture. The present study researches the feasibility of developing a generalized procedure to design unique image recognition systems. These unique image recognition systems will incorporate special purpose processors that will work at a speed that is several orders of magnitude faster than software image processing systems. These systems have great application perspectives, especially in the robotics and industrial fields. One of the most important aspects of these systems-is the unique compact size as compared with other systems of comparable speed. Also, these systems are independent modules that will output, in most cases, a signal to a controller without the need to use a conventional computer or processor. The procedure to be developed provides a new way of designing an image processing system by concentrating on modularity and massive parallelism. Combining the modules will provide a special purpose processing system that achieves object detection and recognition at a high speed not even possible on a general purpose supercomputer. The other advantages include the low cost of implementation and the compact size of the whole system