机器边缘检测形态学操作

Pınar Karakuş
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引用次数: 0

摘要

图像处理是指从图像中获取有用信息并提高图像质量,其关键问题之一是边缘检测。在边缘检测算法中加入形态学算子将如何影响边缘检测性能,是尚未完全解决的问题之一。在这项研究中,Canny 和 Sobel 边缘检测算法被应用于不同的铣刀加工中。对确定的边缘应用了形态算子,并检查了它们对边缘的影响。平均平方误差(MSE)和峰值信号噪声比(PSNR)值用于比较边缘检测算法的性能。根据 MSE 和 PSNR 结果,可以看出 Canny 算法比 Sobel 算法效果更好。此外,得出的结论是,在 Canny 算法和 Sobel 算法中,应用形态学运算后得到的图像比未应用形态学运算的图像性能更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MACHINE WHELL EDGE DETECTION MORPHOLOGICAL OPERATIONS
One of the critical issues of image processing, defined as obtaining useful information from the image and improving the quality of the image, is edge detection. How edge detection performance will be affected by adding morphological operators to edge detection algorithms is among the issues that have not been fully resolved. In the study, Canny and Sobel edge detection algorithms were applied to different milling cutters used in machinability. Morphological operators were applied to the determined edges, and their effects on the edges were examined. Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR) values were used to compare the performances of edge detection algorithms. According to MSE and PSNR results, it was seen that the Canny algorithm gave better results than the Sobel algorithm. In addition, it was concluded that the images obtained as a result of the applied morphological operations provided better performance than the images that were not applied for both Canny and Sobel algorithms.
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