Improved Gamma Corrected Layered Adaptive Background Model

Abstract

This paper proposes a method for pixel-based background subtraction with improved gamma correction and a layered adaptive background model (IGLABM). The main problems of background subtraction are background oscillation and shadow. To solve these problems, we have proposed the gamma corrected layered adaptive background model (GLABM), however the performance of GLABM is not sufficient for real scenes. We hence improve the gamma estimation and prepossessing step of GLABM in this study using the covariance matrix of each pixel. We demonstrate the performance of the proposed improved method by comparing it with GLABM and other pixel-based background subtraction methods.