Intensity Range based Background Subtraction for Effective Object Detection

Abstract

In this letter, we propose an intensity range based object detection scheme for videos with fixed background and static cameras. The scheme suggests two different algorithms; the first one models the background from initial few frames and the second algorithm extracts the objects based on local thresholding. The strength of the scheme lies in its simplicity and the fact that, it defines an intensity range for each pixel location in the background to accommodate illumination variation as well as motion in the background. The efficacy of the scheme is shown through comparative analysis with competitive methods. Both visual as well as quantitative measures show an improved performance and the scheme has a strong potential for applications in real time surveillance.