贴片电阻焊点内部空洞缺陷自适应检测

贴片电阻在回流焊过程中，受工艺影响，焊点内部或多或少会存在空洞缺陷，空洞占比率过高会严重降低器件的可靠性。该文融合局部预拟合(LPF)活动轮廓模型和自适应圆形卷积核，提出一种贴片电阻焊点内部空洞缺陷自适应检测方法。首先，根据贴片电阻图像具有明暗两个明显区域的特点，通过求解区域平均灰度差异最大的优化问题将其自适应地分为较暗和较亮两个区域。然后，针对较暗区域中空洞与背景之间对比度低、空洞分布较稀疏、面积偏大等特点，采用局部预拟合活动轮廓模型进行空洞检测；针对较亮区域中空洞与背景之间差异明显、空洞分布密集、面积偏小等特点，提出一种自适应圆形卷积核检测空洞。最后，采用形状因子和平均灰度策略剔除误检测，实现贴片电阻焊点内部空洞精细检测。实验结果表明，该文算法相较于其他检测算法性能有明显的提升，平均Dice系数高达0.8846。

Adaptive Inspection for Void Defects Inside Solder Joints of Chip Resistors

In the process of reflow soldering, void defects inevitably emerge inside solder joints of chip resistors, which will influence reliability of the device. In this paper, an adaptive inspection method for void defects inside solder joints of chip resistors is proposed by combining a Local Pre-Fitted (LPF) active contour model and circular convolutions with adaptive kernels. First, since the image of chip resistor has two distinct regions, dark and bright regions are adaptively separated from the image after solving the optimization problem with the largest difference between the average gray level values of the two regions. Then, considering low contrast between voids and the image background, sparse distribution and large areas of voids in the dark region, LPF active contour model is used to inspect voids. As for the obvious difference between voids and the image background, dense distribution and small areas of voids in the bright region, circular convolutions with adaptive kernels are proposed to inspect voids. Finally, false detection can be eliminated by the shape factor and an average gray strategy to realize accurate void inspection. Experimental results show that the proposed method is superior to other inspection methods with an average Dice coefficient of 0.8846.