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Tiny Surface Defects on Small Ring Parts Using Normal Maps

机译:使用法线贴图的小环形零件上的微小表面缺陷

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Detection of tiny surface defects on small ring parts remains challenging due to the unnoticeable visual features of such defects and the interference of small surface scratches. This paper proposes a novel method for detecting tiny surface defects based on normal maps of metal parts. To better characterize features of tiny defects and differentiate them from small scratches, we recover the normal map of the metal part through analyzing its directional reflections obtained with our specifically designed directional light units. Based on the normal map, a cascaded detector trained by the AdaBoost approach combined with the joint features and fast feature pyramid is used to localize the defects, achieving fast and accurate detection of tiny surface defects. The proposed method can achieve high detection accuracy with extremely fast speed, only 23 ms per metal part, and comparisons against other methods show our superiority.
机译:由于此类缺陷的视觉特征不明显以及较小的表面划痕的干扰,因此在小环部件上检测微小的表面缺陷仍然具有挑战性。本文提出了一种基于金属零件法线图的微小表面缺陷检测方法。为了更好地表征微小缺陷的特征并将它们与小划痕区分开,我们通过分析使用我们专门设计的定向光单元获得的定向反射来恢复金属零件的法线贴图。根据法线图,通过AdaBoost方法训练的级联检测器结合了关节特征和快速特征金字塔,可以对缺陷进行定位,从而实现对微小表面缺陷的快速,准确检测。所提出的方法可以以极快的速度实现高检测精度,每个金属零件仅23 ms,与其他方法的比较表明了我们的优越性。

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