Moving object detection using an adaptive background subtraction method based on block-based structure in dynamic scene

Today, determining background which forms the basis of the video surveillance system whose use is increasing in parallel with developing technology, is a complicated process to implement for cases involving dynamic scene. In this study, we proposed a block-based adaptive method which can be adaptable to dynamic environmental conditions. By grouping the pixels in the picture frame as 2 × 2 non-overlapped blocks, we reduced the amount of noise and the time delay caused by processing of pixels. By a simple counter structure, we created an adaptive threshold parameter which can be adapted according to the case in N surrounding. We used this parameter to perform an update of the background model and reduced background model normalization process. So, we reduced the update time of background operably. Our proposed method achieved successful results in levels of grey levels.