基于骨架的柔性变形FPC断路检测

为了解决柔性印刷电路(FPC)翘曲变形容易导致图像出现柔性形变现象造成当前的FPC断路检测方法性能降低的问题,在建立柔性形变模型、分析形变机理的基础上,提出了一种基于骨架处理策略的检测方案。首先提取预处理后FPC图像的线路骨架,然后将其输入到建立的动态模板尺度空间(DTSS)模型中,以去除骨架的分支噪声、得到‘纯净’骨架;接着,提取上一步骤处理所得骨架的全部端点,并通过形态学操作和局部模板匹配定位线路异形结构区域,剔除该端点集合中处于异形结构区域内的噪声端点,从而得到断路端点集合,再根据集合中成员与图像位置的对应关系识别断路缺陷。在基于实际环境建立的SUT-F1图库上进行了算法效果验证,并与其他经典方法进行了对比分析。结果表明,本文方法具备良好的抗形变性能,检测正确率(CDR)高达99.30%,误检率(FDR)低至2.25%,表明了方法的有效性;相比于其他方法,CDR至少提高了5.03%,FDR最少降低了8.22%,显示了方法的优势,且具有一定的实际应用价值。

The circuit break detection of flexible deformation FPC based on skeleton

The warping deformation of flexible printed circuit (FPC) would result in flexible deformation of the image acquired, which reduces the detection performance of the system. To solve this problem, this paper propose a solution based on establishing an image flexible deformation model and analyzing deformation mechanism. Firstly, the circuit skeleton is extracted after image pre processing and is delivered to dynamic template scale space (DTSS) model for acquiring clean skeleton image without branches noise. Then, whole endpoints of previous skeleton are extracted and abnormal structure regions are located by morphological operation and local template matching. Endpoints within abnormal structure regions are removed.. Thus, the endpoints of circuit break are acquired, and circuit break defects are detected through the congruent relationship between circuit break endpoints and locations. Experimental results show that the approach proposed in this paper is robust to flexible deformation. The CDR reaches to 99.30% and FDR reaches to 2.25%, which shows the validity of this method. Compared with other methods, CDR increases 5.03% at least, and FDR decreases 8.22%, which shows the advantages of this method in practical application.