Parallel Foreground Object Detection on a Polymorphous Computer

Foreground object detection is an important area in computer vision research. It aims to detect, classify, and recognize object in video images. Real time video processing needs to deal with large amount of data. It is also computationally intensive. This paper presents the parallelization of foreground object detection algorithms on a polymorphous computer that is capable of data parallel, thread parallel and instruction parallel computation. A modified approach using background differentiation and image integration is adopted in this research and a parallel implementation is realized on the PAAG polymorphous array processor. The parallel implementation is able to perform effective real-time foreground object detection in fast video frames. Simulation results show that this approach is highly effective.