Image processing is a task of analysing the image and produces a resultant output in linear way. Image processing tasks are widely used in many applications domains, including medical imaging, industrial manufacturing, entertainment and security systems. Often the size of the image is very large, the processing time has to be very small and usually real-time constraints have to be met. The image analysis requires a large amount of memory and cpu performance, to cope this problem image processing task is parallelized. Parallelism of image analysis task becomes a key factor for processing a huge raw image data. Parallelization allows a scalable and flexible resource management and reduces a time for developing image analysis program. This paper presenting, the automatic parallelization of image processing task in a distributed system, in which suitable subtasks for parallel processing are extracted and mapped with the components of distributed system. This paper presents different design issues of parallel image processing in distributed system. Which helps the image analysis tasks that how to post processing the image in parallel. This technique is quite interactive especially when developing parallel program, as this requires little efforts for finding a suitable distribution of program module and data
