| Summary: | 碩士 === 元智大學 === 工業工程研究所 === 88 === To inspect the quality of solder joints defects needs some special illumination arrangement, such as LED、structural light, or some special instrument, such as X-ray、ultrasonic images. Because these equipments are expensive and can’t inspect solder joints defects effectively, the application for these illumination techniques is limited.
The focus of this study is to provide a solder joints inspection framework based on machine vision. After capturing images which need inspection by a CCD camera, it utilizes the image of copper region on the PCB bare board to apply a minimum-filter, and it can segment all solder joints regions. The selected features of solder joints are calculated for the region. Then the features are separated into two parts: part one is based on the binary images、part two is based on gray-value images. To classify solder joints is using classification tree. In this study, it defines three types of solder joints defects: Open、No solder、Short and regular solder joints.
The experiment results showed that using classification tree determined by the distance between groups and box plots, the classification correctness reached 97.2%. And utilizing the method proposed by Clark and Pregibon(1992), the classified correctness of regular solder joints is 100%, but it would classify Short to regular solder joints.
|
|---|
