Evaluation of global image thresholding for change detection
The objective of this paper is to develop an approach for efficiently and quantitatively evaluating thresholding algorithms for change detection in a surveillance environment. Previous evaluation in the literature has either been subjective or small scale, in part due to the difficulties and/or the time and effort involved in determining appropriate ground truth. In comparison, our automated approach enables us to carry out a more thorough evaluation, and we test the performance of eight different thresholding algorithms using more than 4000 images with two different texture environments.
change detection surveillance ground truth threshold selection performance evaluation