Moving Object Detection Algorithm Based on Gaussian Mixture Model and HSV Space
Aiming at the traditional Gaussian mixture model has poor adaptability to the complex scenes, we proposes an improved moving object detection algorithm based on Gaussian mixture model and HSV space. The motion region is first extracted by the improved three frame difference method. With the matching results, region segmentation of current frame is realized. Then different regions adopt different update strategy that improves the ability to reflect the illumination and scenes change. Next, utilizing characteristics of HSV color space and image first order gradient achieve shadow detection. It effectively reduces interference of shadows, especially the pixels of foreground which has similar brightness properties with background. Experimental results show that the algorithm has good robustness and real time performance.