Welding Wires Centerline Detection Method Based on Image Gradient Segmentation

Zeyu Yang, Dirong Yi
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引用次数: 3

Abstract

One of the key problems in integrated circuit (IC) manufacturing is defect detection of welding wires. In welding wire defect detection, center line extraction is a challenging problem due to the large variance of intensity value along a welding wire as against its background. In this paper, a steger centerline detection technique based on gradient amplitude is proposed for automatic extracting centerlines of welding wires. First, the image of an IC chip with a large length-to-side ratio welding wires is taken using dark field imaging method which is suitable for high dynamic reflectivity objects. Then, contrast stretching and gradient threshold techniques are sequentially used to deal with the problem of greatly varying intensity values along welding wire, which is potentially caused by changing normal vectors of the welding wire. Finally, steger center line extraction method is applied. Primary experimental results indicated that the proposed method is superior to traditional methods including threshold segmentation, maximum entropy threshold, and K-means clustering analysis in terms of conserving connectivity of extracted center lines in challenging situations with largely varying contrast of welding wires.
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基于图像梯度分割的焊缝中心线检测方法
焊丝缺陷检测是集成电路制造中的关键问题之一。在焊丝缺陷检测中,中心线提取是一个具有挑战性的问题,因为沿焊丝方向的强度值与其背景有很大的差异。本文提出了一种基于梯度振幅的steger中心线检测技术,用于焊缝中心线的自动提取。首先,采用适合于高动态反射率物体的暗场成像方法,对具有大长宽比焊丝的集成电路芯片进行成像。然后,依次采用对比拉伸和梯度阈值技术来处理由于导线法向量改变而可能引起的沿焊缝强度值变化较大的问题。最后,采用steger中心线提取方法。初步实验结果表明,在焊缝对比度变化较大的挑战性情况下,该方法在保持提取中心线连通性方面优于阈值分割、最大熵阈值和k均值聚类分析等传统方法。
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