基于视觉的压件形貌特征检测与研究

Inspection and research on the shape feature of pressed parts based on vision

  • 摘要: 针对不规则压件产品人工抽检效率低下且易视觉疲劳等问题,提出了一种基于HALCON视觉软件的压件多特征多重检测方法。该方法根据压件轮廓的多个特征,利用图像灰度化和形态学处理,采用灰度拉伸算法、迭代阈值算法等提取和分割轮廓,并对分割后的轮廓特征进行属性判断,采取最小二乘法拟合,精准地检测压件的特征。采集100个压件产品利用上述方法进行检测,检测的准确率达到97%。实验表明这种压件检测方法适用于复杂多个特征的压件形貌检测,对压件外形容忍度较高,检测速率快,满足工业上对此类精密产品的高效检测要求。

     

    Abstract: Aiming at the problems of inefficient manual sampling of irregular pressed parts and easy visual fatigue, a multi-feature and multiple detection method for pressed parts based on HALCON vision software is proposed. According to multiple features of the contour of the pressed part, this method uses image gray-scale and morphological processing, uses gray-scale stretching algorithm, iterative threshold algorithm, etc. to extract and segment the contour, and judge the attributes of the segmented contour feature, and take the minimum The two-fold fitting method can accurately detect the features of the pressed parts. Collect 100 pressed products and use the above-mentioned method to detect, and the detection accuracy rate reaches 97%. Experiments show that this pressing part detection method is suitable for pressing parts with complex and multiple features. It has a high tolerance to the shape of the pressed parts and a fast detection rate, which meets the high-efficiency inspection requirements for such precision products in the industry.

     

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