Automated visual inspection of surface mounted chip components

In order to develop the reliable and fast visual inspection techniques for surface mounted components after they have been placed in wet solder paste on a printed circuit board (PCB). An inspection process based on machine vision is presented. First, with an adaptive segmentation method based on local valley, the binary component electrodes were obtained, at the same, the location of the component was gotten by the sliding location window algorithm, then, the defects such as component missing, component rotation and component shift are detected by analyzing the projection information of the electrodes. Second, the three color features are extracted from the component body and the Bayes classifier is used to inspect whether the components body is wrong. The experiment results have verified the validity of this scheme in terms of recognition rate and speed.