Improved HSV-based gaussian mixture modeling for moving foreground segmentation

Abstract

It is crucial to get the moving foreground for variety video processing system in complex scenes. An improved GMM-based method is developed that can real-time segment moving foreground efficiently. The Gaussian mixture model is improved to effectively detect motion foreground objects even if the object moves slowly. Some relationships between H and S components in HSV space are adopted to suppress shadow caused by moving objects. The shortcoming in literature that more parameters are needed to remove shadow. Experimental results highlight that the proposed method is computationally cost-effective and robust to segment foreground by comparison. © 2012 Springer-Verlag Berlin Heidelberg.