关键词: 边缘检测, Stevens定理, 非最小值抑制, Pillar K-means算法, 最大值滤波

Abstract: Concerning the thresholds often being needed in the image edge detection and it is difficult to set good threshold values for the variant illumination image, a new edge detection method was proposed to solve these problems. Firstly, according to the logarithm, an image was decomposed into high frequency and low frequency, and the high frequency image was extracted by the logarithmic image minus the image by the maximum value filter. Then based on the Stevens theorem from cognitive psychology, the high frequency information was transformed into visual psychological quantity. After the edges were thinned by non-minimum suppression, they were extracted by Pillar K-means algorithm. The proposed method has good effect on the variant illumination image and does not need to set threshold value. The experimental results prove the effectiveness of the proposed method, and also show that the edge value in variant intensity may be agreed by converting the intensity to the psychological value.

Key words: edge detection, Stevens theorem, non-minimum suppression, Pillar K-means algorithm, maximum value filtering