Real-Time Object Detection in Parallel Through Atomic Transactions

Object detection and tracking is important operation involved in embedded systems like video surveillance, Traffic monitoring, campus security system, machine vision applications and other areas. Detecting and tracking multiple objects in a video or image is challenging problem in machine vision and computer vision based embedded systems. Implementation of such an object detection and tracking systems are done in sequential way of processing and also it was implemented using hardware synthesize tools like verilog HDL with FPGA, achieves considerably lesser performance in speed and it does support lesser atomic transactions. There are many object detection and tracking algorithm were proposed and implemented, among them background subtraction is one of them. This paper proposes an implementation of detecting and tracking multiple objects based on background subtraction algorithm using java and .NET and also discuss about the architecture concept for object detection through atomic transactional, modern hardware synthesizes language called Bluespec.