Background subtraction algorithm and image skeletonization based anomaly event detection for low resolution video

Video surveillance system is a major research area of image processing applications. Generally, Low resolution Camera is used for surveillance and thus processing a digital image recorded by such low resolution camera is a challenging task in case of object recognition. A system for low cost, less computation automatic identifying and tracking of objects and events in the low resolution video is presented. The proposed video analyzing system provides best solution by using BGS algorithm, image skeletonization technique and SVM. Experimental results which illustrate this system is optimal for real time applications in video surveillance.