X-ray inspection of TSV defects with self-organizing map network and Otsu algorithm
X-ray inspection of TSV defects with self-organizing map network and Otsu algorithm
复制标题
利用自组织映射网络和 Otsu 算法对 TSV 缺陷进行 X 射线检测
DOI：
10.1016/j.microrel.2016.10.011
复制
发表时间：
2016-12-01
影响因子：
1.6
通讯作者：
Liao, Guanglan
中科院分区：
文献类型：
--
作者：
Shen, Junjie;Chen, Pengfei;Liao, Guanglan
直通硅通孔(TSV)是3D集成中最关键的元件之一，其中底部未填充和孔洞等缺陷非常常见。因此，缺陷检测对提高产品质量具有重要意义。本文介绍了一种基于X射线成像的TSV缺陷无损检测方法。从图像中提取7个代表TSV的特征，然后输入自组织映射(SOM)网络进行分类测试。结果表明，SOM网络可以很好地区分正常TSV和缺陷TSV。利用OTSU算法对TSV内部的空洞进行了进一步的定性定位，并通过扫描电子显微镜图像进行了验证。证明了SOM网络和OTSU算法用于TSV缺陷X射线检测的可行性。(C)2016爱思唯尔有限公司。保留所有权利。
Through-silicon via (TSV) is one of the most critical elements in 3D integration, where defects such as unfilled bottom and holes are very common. Thus, defect detection is of great importance to improve products quality. In this work, a non-destructive TSV defect detection method using X-ray imaging is introduced. Seven features representative of TSVs are extracted from the images, and then inputted into a self-organizing map (SOM) network for classification and testing. The results demonstrate that the normal TSVs and defective TSVs can be distinguished obviously by SOM network. The voids inside the TSVs are further located qualitatively using the Otsu algorithm and verified by the SEM images. These prove the feasibility of X-ray inspection of TSV defects with SOM network and Otsu algorithm. (C) 2016 Elsevier Ltd. All rights reserved.