AUTOMATIC THRESHOLDING BASED ON HUMAN VISUAL-PERCEPTION

An automatic thresholding method based on aspects of the human visual system which preserved edge structure in images is proposed. We first determine edge thresholds based on human visual perception, and then use these edge thresholds to find several edge intervals. From these edge intervals, we find the threshold value(s) at which most edge information is preserved in the thresholded image. A bilevel thresholding algorithm is first described, and then two multilevel thresholding algorithms called N(m)-multilevel thresholding and mN-multistep thresholding arc derived through a slight modification of the bilevel thresholding algorithm. The multistep thresholding algorithm directly uses bilevel thresholding sequentially to select m threshold values one by one so as to speed up the thresholding process. The proposed thresholding method is simple, requiring neither an iterative operation nor edge detection.