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首页> 外文期刊>IEEE transactions on industrial informatics >A Novel Self-Feedback Intelligent Vision Measure for Fast and Accurate Alignment in Flip-Chip Packaging
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A Novel Self-Feedback Intelligent Vision Measure for Fast and Accurate Alignment in Flip-Chip Packaging

机译：用于倒装芯片封装的快速准确对准的新型自助式智能视觉措施

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摘要

A template matching (TM) algorithm has been widely employed in a visual inspection process of wafer-level flip-chip packaging, but the structures of traditional TM algorithms are always direct feedforward, which leads to the difficulty in achieving fast speed and high accuracy at the same time. The motivation of this article is to combine the ability to enable the chip visual measurement running in a fast-speed and high-accuracy manner. First, a novel self-feedback intelligent template matching (SFI-TM) structure is proposed, which can enable the intermediate information in the matching process to be fully utilized. The intelligent speed and resolution regulation rules are combined to construct the SFI-TM algorithm. Then, the reliability and robustness of the SFI-TM algorithm are theoretically analyzed to make sure it works in a stable manner. Finally, a series of practical chip alignment visual inspection experiments, including parameter testing, comparing experiments with the other five proposed visual detection algorithms, and robustness testing, are carried out in detail, respectively. The experimental results indicate that the SFI-TM algorithm can achieve the highest average measurement accuracy (1.08 mu m) with almost the same measurement speed as fast as Tiny YOLOv2, and that it can resist the brightness variation from -20 to 30 gray value, the pepper-salt noise with a density of 0.5/pixel, and the Gaussian noise with a large variance of 2.5. In addition, it has good robustness against blurring and distortion of images under the dynamic speed motion processes.
机译：模板匹配（TM）算法已广泛采用晶圆级倒装芯片封装的目视检查过程，但传统TM算法的结构始终是直接的前馈，这导致实现快速速度和高精度的难度同时。本文的动机是将能够以快速和高精度的方式运行芯片视觉测量的能力。首先，提出了一种新颖的自助式智能模板匹配（SFI-TM）结构，其可以使匹配过程中的中间信息能够充分利用。智能速度和分辨率调节规则组合以构建SFI-TM算法。然后，理论上分析了SFI-TM算法的可靠性和鲁棒性，以确保其以稳定的方式工作。最后，一系列实际芯片对准视觉检查实验，包括参数测试，比较与其他五个所提出的视觉检测算法和鲁棒性测试的实验，以及鲁棒性测试。实验结果表明，SFI-TM算法可以达到最高的平均水平测量精度（1.08 mu m），与微小的yolov2具有几乎相同的测量速度，并且它可以抵抗-20到30幅灰度值的亮度变化，密度为0.5 /像素的辣椒噪声，高斯噪声具有大方差为2.5。此外，它具有良好的鲁棒性对动态速度运动过程下的图像的模糊和变形。

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  • 来源
    《IEEE transactions on industrial informatics》 |2020年第3期|1776-1787|共12页
  • 作者

    Wu Zelong; Tang Hui; Feng Zhaoyang; Wang Weimin; He Sifeng; Gao Jian; Chen Xin; He Yunbo; Chen Xun;

  • 作者单位

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

    Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipmen Guangzhou 510006 Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Alignment; flip-chip packaging; self-feedback; template matching (TM); visual measurement;

    机译：对齐;倒装芯片包装;自我反馈;模板匹配（TM）;视觉测量;

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