An Image Thresholding Method Based on Human Visual Perception

A novel thresholding method based on human visual perception is presented in this paper. The method first utilizes statistical characteristics of an image to choose two gray levels as candidate thresholds by the properties of human visual perception, and then determines the one having minimum standard deviation sum as the optimal threshold. Choice of candidate thresholds reduces search space of thresholds and accelerates threshold selection. The proposed method was compared with several classic thresholding methods on a variety of nondestructive testing (NDT) images and general real world images, and experimental results show its effectiveness and efficiency.