PCBA (printed circuit board assembly)元器件边缘检测的完整度直接影响装配机器人对元器件尺寸及其间隙的视觉测量精度。针对Canny算子提取密集区域目标边缘存在明显的边缘粘连和断缺现象的问题,提出一种具有高完整度的PCBA元器件边缘检测新方法。首先针对原Canny算子依据像素点灰度值梯度确定的边缘像素点,提出3×3邻域窗自适应阈值非极大值抑制方法,以有效避免密集区相邻边缘粘连;其次依据EPGVF Snake模型参数化后Snake曲线的梯度场,结合边缘保真项,提出边缘是否发生断缺的邻域窗自适应判断方法; 最后采用像素置换模板对断缺的边缘像素进行填充,以有效保留细弱边缘、避免断缺发生。实验结果表明,本文方法能有效避免PCBA密集区元器件边缘粘连和细弱边缘断缺,边缘完整度较其他方法提高了约15.5%。

The integrity of edge detection of printed circuit board assembly (PCBA) components directly affects the visual measurement accuracy of the size and gap of components obtained by assembly robots. Aiming at the problem that the edges of objects in dense areas extracted by the Canny operator have obvious edge adhesion and missing phenomena, a new method of PCBA component edge detection with high integrity is proposed. First, for the edge pixels determined by the original Canny operator based on the gradient of the pixel gray value, an adaptive threshold non-maximum suppression method with a 3×3 neighborhood window is proposed to effectively avoid the adhesion of adjacent edges in dense areas. Second, based on the gradient field of the Snake curve after parameterization by the EPGVF Snake model, combined with the edge fidelity term, a neighborhood window adaptive judgment method for determining whether the edge is broken is proposed. Finally, a pixel replacement template is used to fill the broken edge pixels to effectively retain the weak edges and avoid breaks. Experimental results show that the proposed method can avoid the adjacent edge adhesion and weak edge missing effectively in the dense area of PCBA, and the integrity of the preserved edge is improved about 15.5% compared to other methods.