Background modelling by codebook technique for Automated Video Surveillance with Shadow Removal

Background modelling is a technique used for object detection by modelling the background of a video sequence. This technique is applied for monitoring in a surveillance application purpose. The technique should be robust in detecting the object in crucial condition. The internal model should sensitive to detect all moving objects by satisfying its challenging aspects. The important aspect of background modelling are local and global illumination variation, motion changes, presence of shadows, camouflage, some changes in background geometry and high frequency. Basic principle of background modelling is background subtraction, where the motion segmentation is done. During the motion segmentation, getting accurate or correct shape of the object is one of the prime challenges. While light is occlude by object, a shadow forms. During motion segmentation, it is detected as foreground object, which is disaster of motion algorithm. In our project, we have projected a Background Modelling Technique with Shadow Removal for Automated Video Surveillance System. The Algorithm has been tested by considering different datasets. Experimental results validate the implemented algorithms.