Unsupervised image change detection means based on 2-D entropy

In this paper, a novel image change detection means based on 2-D histogram formed by pixel gray levels and the local average gray levels is proposed. First, the 2-D histogram is segmented by a line passing through the diagonal of 2-D histogram in a certain direction. Second, the improved 2-D entropy is defined to acquire the optimal segmentation direction and the optimal threshold. And the 2-D histogram is segmented into unchanged region and change region. Then the change area is detected based on the change region of 2-D histogram. Finally, the change detection means is compared to traditional means Theoretical analysis and experiment result show that this algorithm is more accurate on detection precision and faster on detection speed.