A Texture-Based Method for Goods Monitoring of Video Surveillance

Goods monitoring is an important item of video surveillance, which is necessary to run automatically in practice. Two incidents of goods monitoring including goods stolen and broken are considered in this paper. Following the process of video surveillance, a texture-based method is proposed to deal with the incidents. The main idea is to divide the image of each objective blocks into several regions equally. The texture refreshing of each region is investigated during monitoring, which means special texture status identifies the detection of goods stolen and broken. Several surveillance videos are tested, and the results indicate the proposed method and model are efficient, high detection-rate and robust. Finally, the proposed method is introduced to a intelligence video surveillance.