Two-Counter Method on Background Registration for Moving Object Segmentation

In this thesis, we designed a two-counter background registration method on moving object segmentation which is an important front-end process for human activity recognition.
In moving object segmentation, we can use histograms of different values to determine the threshold value for automatic noise elimination in different picture frames. Moving objects are separated from the background in the current frame effectively with the proposed threshold method. The morphological operator is then used to eliminate the background noise of the segmentation results and shadows of the moving objects. Finally, we use the statistic conception to update the background information. We propose the Two-Counter background registration algorithm to reconstruct the reliable background information effectively for different surveillance environments.