基于全局对比度和边缘梯度的印刷辊表面缺陷检测算法

Bilong Li, Shaozhong Cao, Changfu Xu, Shuang Huang
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引用次数: 0

摘要

针对印刷辊复杂的表面状况,提出了一种基于全局对比度和边缘梯度的缺陷突出算法。该算法利用伽马变换对图像的整体亮度进行调整,然后通过LC算法得到显著性图;同时对初始图像进行Canny边缘检测,再进行形态学运算得到另一幅显著性图。最后,利用图像融合算法将两种算法得到的图像进行融合,得到最终的缺陷显著性图,完成显著性检测。实验结果表明,该算法具有较高的识别率和准确率,能够满足印刷辊表面缺陷检测的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surface defect detection algorithm for printing roller based on global contrast and edge gradient
In view of the complex surface condition of printing roller, a defect salience algorithm based on global contrast and edge gradient is proposed. This algorithm uses gamma transform to adjust the overall brightness of the image, and then obtains a salience map by LC algorithm; at the same time, Canny edge detection is performed on the initial image, and then morphological operation is performed to obtain another salience map. Finally, image fusion algorithm is used to fuse the images obtained by the two algorithms to get the final defect salience map and complete the salience detection.The experimental results show that the algorithm has high recognition rate and accuracy, which can meet the needs of surface defect detection of printing roller.
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