A Region-Based Normalized Cross Correlation Algorithm for the Vision-Based Positioning of Elongated IC Chips
A Region-Based Normalized Cross Correlation Algorithm for the Vision-Based Positioning of Elongated IC Chips
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DOI：
10.1109/tsm.2015.2430453
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发表时间：
2015-05
影响因子：
2.7
通讯作者：
Buyang Zhang;Hua Yang;Z. Yin
中科院分区：
文献类型：
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作者：
Buyang Zhang;Hua Yang;Z. Yin
随着集成电路(IC)芯片的发展，许多具有少量织构的细长芯片开始用于IC的封装和制造。传统的模板匹配方法不能有效地定位这些芯片；这种限制导致IC设备无法准确地拾取细长的IC芯片，或者可能将不工作的IC芯片封装到电子设备上。提出了一种新的基于区域的归一化互相关算法，该算法利用信号函数来分离芯片和背景像素信息的影响。为了获得更快的速度，利用IC芯片的包围盒来快速估计IC芯片在目标图像中的感兴趣区域。利用LED分选设备进行的各种实验表明，该算法能够正确定位细长IC芯片，并能以合理的精度区分好的芯片和不工作的芯片。当目标图像的大小为512×512像素，而模板图像的大小小于140×140像素时，该算法的匹配时间小于14ms。该算法在IC封装领域具有广阔的应用前景。
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.