大气与环境光学学报 ›› 2019, Vol. 14 ›› Issue (4): 313-320.

• 光电技术 • 上一篇    

QFN芯片表面划痕检测定位方法设计

张若楠1,2,沐超1,张固1,2,刘小勤1   

  1. 1 中国科学院安徽光学精密机械研究所中国科学院大气光学重点实验室 安徽合肥 230031;
    2 中国科学技术大学, 安徽合肥 230026
  • 收稿日期:2018-04-13 修回日期:2018-05-17 出版日期:2019-07-28 发布日期:2019-07-12
  • 通讯作者: 刘小勤

Method of Surface Scratch Detection and Location of QFN Chip

  • Received:2018-04-13 Revised:2018-05-17 Published:2019-07-28 Online:2019-07-12

摘要: 在工业应用中,需要对方形扁平无引脚封装(Quad flat no-lead package, QFN)芯片表面划痕实时
准确检测,提出了一种快速的芯片表面划痕检测定位方法。通过图像分割算法获取缺陷图像,结合
轮廓提取算法可以较好地实现芯片表面划痕定位。同时,为了保证对芯片表面划痕实时检测,采用
基于粒子群的Otsu多阈值算法进行图像分割,不仅使得图像中缺陷区域更加明显,而且缩短了芯片
表面划痕检测时间。与直接采用Otsu算法相比,芯片表面划痕检测时间由秒级缩短至毫秒级,提高
了芯片质量检测效率。该划痕快速定位检测方法对芯片检测设备软件系统开发与应用具有重要的参考价值。

关键词: 方形扁平无引脚封装芯片, 划痕检测, 多阈值分割, 粒子群优化算法

Abstract: In industrial applications, it is necessary to accurately detect scratches on the
surface of a quad flat no-lead package (QFN) chip in real time. A rapid chip
surface scratch detection and location method was proposed. According to image
segmentation algorithm, a defect image can be acquired firstly. Then by combining
with the contour extraction algorithm, the chip surface scratch location can be
achieved. At the same time, in order to ensure real-time detection of scratches
on the chip surface, image segmentation is further completed by using the
Otsu multi-threshold algorithm based on particle swarm optimization (PSO)
algorithm, which not only makes the defect area in the image more obvious,
but also shortens the scratch detection time on the chip surface. Compared
with the direct use of the Otsu algorithm, the scratch detection time on the
chip surface is reduced from seconds to milliseconds, and the chip quality
detection efficiency has been improved greatly. It is shown that the method
has important reference value for the development and application of
software systems for chip detection equipment.

Key words: quad flat no-lead package chip, scratch detection, multi-threshold segmentation, particle swarm optimization algorithm

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