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 back ground, 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.