Using Temporal-spatial Analysis and Background Subtraction Method to Detect Moving Objects in the Video Sequence

[[abstract]]The critical issues of motion detection based on computer vision are the noises in the dynamic background and the noises from objects’ moving in the foreground. These two noises are more obvious, especially at using background subtraction method. In this study, A method that combined with temporal-spatial and color information is used to improve the detection accuracy. The method can be divided into three sections: (1) The time-varying updated background is built by temporal statistic histogram; (2) Three dimension color information is transferred into two dimension color phase and color intensity by angle-module rule. Next, moving objects in the foreground are extracted by adaptive background subtraction, and the noises (shadows and small change) are removed according to variations of color information in the background and foreground; (3) Dynamic background noises (ex: branches movements and rain interferences) are removed by the concept combined with temporal and spatial information of video sequences. As the results present, our accuracy of the detection is upper than ninety percentage in the outside and inside environments. The system also has good performance when the false detection is caused by shadows, dynamic background noises, and camera shakings.