MODELING AND SIMULATION OF PARALLEL PROCESSING ARCHITECTURE FOR IMAGE PROCESSING

Typical real time computer vision tasks require huge amount of processing power and time for handling real time computer vision applications. The nature of processing in a typical computer vision algorithm usually ranges from many small arithmetic operations (Fine Grain Parallelism) to symbolic operations (Coarse grain parallelism). The task become more complicate while considering image processing application due to large data sets and there processing. The existing processing system responds efficiently under sequential working and result in efficient output, but results in a slow operating system which results in a inefficient processing system under high speed image processing systems. Parallel processing founds to be the only solution to obtain the require processing speed for handling high-speed image processing applications. The existing image processing systems support usually only one suit of operations at once and fail to respond under multiple tasks. System taking single instruction or multiple instruction process operates using low level and high-level operations. Generally SIMD architecture is suitable under low level processing while MIMD architecture is suitable for high-level processing. This paper explores on modeling and simulation of parallel Image Processing architecture for Image Processing applications using Parallel Virtual Machine(PVM) , MATLAB external interface API and C language on the Linux operating system platform.