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The evaluation of normalized cross correlations for defect detection

机译:用于缺陷检测的归一化互相关的评估

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摘要

The normalized cross correlation (NCC) has been used extensively in machine vision for industrial inspection, but the traditional NCC suffers from false alarms for a complicated image that contains partial uniform regions. In this paper, we study the use of NCCs for defect detection in complicated images. The performance of NCCs in monochrome and color images, and the effect of image smoothing are empirically evaluated. The proposed NCC in a smoothed color image can effectively alleviate false alarms in defect detection applications.
机译:标准化互相关(NCC)已在机器视觉中广泛用于工业检查,但是传统NCC会因包含部分均匀区域的复杂图像而出现误报。在本文中,我们研究了使用NCC在复杂图像中进行缺陷检测。根据经验评估了NCC在单色和彩色图像中的性能以及图像平滑效果。在平滑的彩色图像中提出的NCC可以有效地减轻缺陷检测应用中的虚假警报。

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