A Modified Gray level Co-occurrence Matrix based Thresholding for Object Background Classification

Object background classification is the basic problem of object tracking in the computer vision area. Thresholding is the simplest approach to separate object from the background. The solutions using thresholding techniques become more complex when the image is blurred or low contrast. In this paper, we proposed a modified co-occurrence matrix for extraction of the edge information to detect the threshold for object and background classification in a low contrast or blurred image. The proposed approach is tested with standard test images which are of low contrast or blurred to different degree to validate the efficiency of our proposed method.