Background Construction of Video Frames in Video Surveillance System Using Pixel Frequency Accumulation

Moving object detection has been widely used in diverse discipline such as intelligent transportation systems, airport security systems, video monitoring systems, and so on. In this paper we proposed an edge segment based statistical background modeling algorithm, which can be implemented for moving edge detection in video surveillance system using static camera. The proposed method is an edge segment based, so it can help to exceed some of the difficulties that face traditional pixel based methods in updating background model or bringing out ghosts while a sudden change occurs in the background.As an edge segment based method it is robust to illumination variation and noise, it is also robust against the traditional difficulties that faces existing pixel based methods like the scattering of the moving edge pixels. Therefore they can’t utilize edge shape information. Some other edge segment based methods treat every edge segment equally creating edge mismatch due to non stationary background. The proposed method found elegant solution to this lake by using a model that uses the statistics of each background edge segment, so that it can model both the static and partially moving background edges using ordinary training images that may even contain moving objects.