ADAPTIVE THRESHOLD BACKGROUND SUBTRACTION FOR DETECTING MOVING OBJECT ON CONVEYOR BELT

Moving object detection is an important task in many computer vision classifications applications. The goal of this study is to identify a moving object detection method that provides a reliable and accurate identification of objects on the conveyor belt. In this paper, a study of the moving object detection methods is presented. Firstly, moving object detection pixel by pixel was performed using background subtraction, frame difference method. The threshold value in both background subtraction and frame difference is a fixed value, which determines the accuracy of object identification. The adaptive threshold values were calculated for both the methods to improve the accuracy. The performance of these methods was compared with the ground truth image.