毕业设计论文 运动目标检测中阴影去除算法的研究与实现

Research and realization of the shadow removing algorithm for

Moving object detection

Abstract Development of the computer vision technology, the electronic and the communication technology, has made the intelligent visual surveillance system an increasingly important safe defense way. Because it has advantages of higher quality and less need of investment. So it has cheerful prospect in the applications of surveillance for traffic, bank, hotel, shopping, etc.

Both its history and current situation is summarized here, then, a research was made for the key technology of the segmentation of moving objects and the detection and removal of shadows.

As the initial stage in the visual data processing, moving object detection is a key point. After carefully study of moving object detection methods used presently, a more reliable algorithm is determined, that is, the mixed Gauss model. It was adopted to detect moving objects.

As external factors such as sunlight and lighting effects，resulting in extraction of moving foreground often contain shadow. So, shadows detection and elimination of moving objects is essential to the post-processing such as objects tracking, classification and recognition. The existence of shadow will allow the above-mentioned post-processing to fail. In order to remove the shadow of object foreground, this paper first analyze the mechanism of the shadow produced, understand the characteristics of the shadow and the human visual characteristics, then, a method of shadow detection based on the RGB color model is proposed on the basis of these characteritics and the summary and analysis for various shadow detection. We have conducted many experiments to verify the proposed approach. The results show that the algorithm can detect moving targets to remove the shadow, and easy to implement.

Key words Visual Surveillance; Moving Object Detection; Mixed Gaussian Model; RGB color model; Shadow Removal