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所属单位：电子信息工程学院

发表刊物：Huanan Ligong Daxue Xuebao

摘要：In order to meet the high-speed and high-accuracy demands of the machine vision-based measurement system of cutting tool sizes, an image sub-pixel edge detection method based on Arimoto entropy of linear intercept histograms and Zernike moment is proposed. In the method, first, the neighborhood-average grayscale of images is obtained through the Gaussian sliding window to construct a two-dimensional histogram, and the linear intercept method is adopted to reduce the two-dimensional histogram to a one-dimensional histogram. Then, aiming at the achieved linear intercept histogram, the thresholding is performed according to the Arimoto entropy, and the obtained threshold is mapped back to the two-dimensional histogram to extract a target region and pixel-level edges. Finally, the edge points are re-located by using the Zernike moment-based edge model, thus achieving the sub-pixel-level edges of cutting tool images. By a large number of experiments on the cutting tool images, the proposed method is compared with the Canny-based, the space moment-based, the gray moment-based and the Zernike moment-based edge extraction methods. The results show that the proposed method is superior in both speed and accuracy. © 2017, Editorial Department, Journal of South China University of Technology. All right reserved.

ISSN号：1000-565X

是否译文：否

发表时间：2017-12-01

合写作者：龙云淋,周杨

通讯作者：吴一全