改进SSD芯片缺陷检测算法的研究与应用

L. Zhi, Zhou Bo
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引用次数: 0

摘要

缺陷检测是发光二极管(LED)生产过程中的一个重要环节。在生产环境中,需要检测的缺陷大多是32×32像素以下的小目标,目前的SSD算法无法有效检测到。基于反卷积单镜头检测器(Deconvolutional Single Shot Detector, DSSD)算法的概念,提出了一种改进的单镜头检测器(Single Shot Detector, SSD)芯片缺陷检测方法,用于精确检测LED芯片表面缺陷。首先,将原算法的基础网络VGGNet替换为ResNet,去掉第一池化层;然后加入预测模块和反褶积模块,实现高、低层语义信息融合;最后,对模型隐藏层进行剪枝,去掉最后一个卷积层和反卷积模块。实验结果表明,与原有的SSD算法相比,该算法提高了芯片缺陷检测的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and Application on the Improved SSD Chip Defect Inspection Algorithm
Defect inspection is an important part of the light-emitting diode (LED) production process. In the production environment, most of the defects to be inspected are small targets below 32×32 pixels, which cannot be detected by current SSD algorithm effectively. Based on the concept of DSSD (Deconvolutional Single Shot Detector) algorithm, an improved SSD (Single Shot Detector) chip defect inspection method is proposed to accurately inspect LED chips surface defects. First, the original algorithm’s basic network VGGNet is replaced by ResNet, and the first pooling layer is removed; then a prediction module and a deconvolution module are added to fuse the semantic information between the high-level and low-level; finally, model hidden layer is pruned, and the last convolution layer and deconvolution module are removed. The experimental results show that compared with the original SSD algorithm, which enhances the accuracy of chip defect inspection.
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