The new visual inspection systems techniques using real time machine vision replace the human visual\nmanual inspection on PCB flux defects, which brings harmful effects on the board which may come in\nthe form of corrosion and can cause harm to the assembly. In short, it brings improvement in Printed\nCircuit Boards (PCB) production quality, principally concerning the acceptance or rejection of the\nPCB boards. To develop new algorithm in image processing which detects flux defect at PCB board\nduring re-flow process and achieve good accuracy of the PCB quality checking. The machine will be\ndesigned and fabricated with the total automation control system with mechanical PCB loader/unloader,\npneumatic system handler with vacuum cap, vision inspection station and final classification\nstation (accept or reject). The image processing system is based on shape (pattern) and color image\nanalysis techniques with Matrox Imaging Library. The shape/texture of the PCB pins is analyzed by\nusing pattern matching technique to detect the PCB flux defect area. The color analysis of the flux\ndefect in a PCB boards are processed based on their red color pixel percentage in Red, Green and Blue\n(RGB) model. The red color filter band mean value of histogram is measured and compared to the\nvalue threshold to determine the occurring on the PCB flux defects. The system was tested with PCB\nboards from factory production line and achieved PCB board flux defects sorting accuracy at 86.0%\nbased on proposed pattern matching technique combined with red color filter band histogram.
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