Author : Amit H. Choksi, Ronak Vashi, Mayur Sevak and Kaushal Patel

Electronic manufacturing industry, the printed circuit board manufacturing is basic requirement. One of the backbones in electronic manufacturing industry is the printed circuit board (PCB) manufacturing. Due to the human limited resources and speed requirements, manual inspection is ineffective to inspect every printed circuit board. Image difference operation is frequently used in automated printed circuit board (PCB) inspection system as well as in many other image processing applications. This inspection of PCB consists of mainly missing or wrongly placed components in the PCB. If there is any missing electronic component then it is not so damaging the PCB. But if any of the component that can be placed only in one way and has been soldered in other way around, then the same will be damaged and there are chances that other components may also get damaged. To avoid this, a PCB inspection is in demand that may take care of the missing or wrongly placed electronic components. Hence, this paper presents an efficient algorithm for an automated visual PCB inspection system that detects and locates any defect found on PCBs. The PCB inspection system is then improved by incorporating a geometrical image registration, minimum thresholding technique and median filtering in order to solve alignment and uneven illumination problem. Finally, defect classification operation is employed in order to identify the source for six types of defects namely, missing hole, pin hole, under etch, short-circuit, mouse bite, and open-circuit. The goal of this technique is to enhance the image difference operation in term of computation time using wavelet transform techniques like a dB1, dB2, dB3 and dB4 wavelets.

Keywords: PCB defects; Wavelet Decomposition; Thresholding; Image Difference operation

Article published in International Journal of Current  Engineering  and Technology, Vol.4,No.4 (Aug- 2014)