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Robust and consistent defect size measuring method in Automated Vision Inspection system

机译:自动视觉检测系统中稳健一致的缺陷尺寸测量方法

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Automatic vision inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on same defect with some variations on position or rotation mainly because we get different image. It is caused by possible variations from image acquisition process including optical factors, non-uniform illumination, random noises, and so on. For this reason, conventional area based defect measuring method has a problem on robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem. We utilize volume information which is completely ignored in the area based defect measuring method. We choose a cylinder shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness and consistency of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect.
机译:自动视觉检查(AVI)系统可自动检测缺陷特征并通过摄像头视觉测量其尺寸。 AVI系统通常会报告同一缺陷的不同测量结果,并且位置或旋转度会有一些变化,这主要是因为我们得到了不同的图像。这是由于图像采集过程中可能出现的变化引起的,包括光学因素,照明不均匀,随机噪声等。因此,常规的基于面积的缺陷测量方法存在鲁棒性和一致性的问题。在本文中,我们提出了一种新的缺陷尺寸测量方法来克服这个问题。我们利用在基于面积的缺陷测量方法中被完全忽略的体积信息。我们选择圆柱形状作为实验的缺陷模型。结果表明,我们提出的方法显着提高了缺陷尺寸测量的鲁棒性和一致性。给定适当的建模,建议的基于体积的测量方法可以应用于各种类型的缺陷。

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