SMT stencil automatic registration method based on coordinates distribution analysis

Abstract

Since the stencil image used for surface mount technology (SMT) always has various defects such as less holes and burrs in the laser processing and imaging, it is indispensable to detect those flaws with high accuracy. An automatic registration lies at the root of identifying defects. In this paper, a novel automatic registration algorithm for stencil images is proposed. According to the distribution probability density of the coordinates of gravity center points in a stencil image, the adaptive parameter DBSCAN clustering algorithm is adopted to classify those points. As a result, we could find corresponding gravity center points (feature points) in the stencil image and its standard design file respectively. A transformation matrix between the stencil image and its standard design file is obtained by the feature points. Experiments have shown that this automatic registration algorithm can be well adapted to the stencil images with random defects.