A Region-Based Normalized Cross Correlation Algorithm for the Vision-Based Positioning of Elongated IC Chips

With the development of integrated circuit (IC) chips, many elongated chips with small amounts of textures have begun to be used in IC packaging and manufacturing. Traditional template-matching methods are not effective for positioning these chips; this limitation results in IC equipment that cannot accurately pick up an elongated IC chip or may package a nonworking IC chip onto an electronic device. In this paper, a novel region-based normalized cross correlation algorithm that uses a signal function to separate the influences of the IC chip and the background pixel information is proposed. To obtain an increased speed, the bounding box of the IC chip is employed to rapidly estimate the region of interest of an IC chip in a target image. Various experiments using LED sorting equipment demonstrate that our algorithm results in correct positioning for elongated IC chips and can distinguish good chips from nonworking chips with reasonable accuracy. When the size of the target image is 512 × 512 pixels and the size of the template image is smaller than 140 × 140 pixels, the matching time of our algorithm is less than 14 ms. This algorithm may have many applications in the field of IC packaging.