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Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location

机译:用于晶体管光子发射分析的无监督图像处理方案,以识别缺陷位置

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The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot's intensities. In order to improve the identification of all of the photon emission spots, we introduce an unsupervised processing scheme. It is based on iterative thresholding decomposition (ITD) and mathematical morphology operations. It unveils all of the emission spots and removes most of the noise from the database thanks to a succession of image processing. The ITD approach based on five thresholding methods is tested on 15 photon emission databases (10 real cases and 5 simulated cases). The photon emission areas' localization is compared to an expert identification and the estimation quality is quantified using the object consistency error. (C) 2015 SPIE and IS&T
机译:对高比例互补金属氧化物半导体(CMOS)集成电路(IC)中晶体管发出的光的研究已成为分析故障设备,跟踪故障根本原因并确定从何处开始的关键方法。物理分析。 IC中缺陷区域的定位对应于可靠性检查,并向设计人员提供信息以改善IC设计。 CMOS的缩放导致获取区域内的活动节点的数量增加。斑点强度之间也存在更多差异。为了改善对所有光子发射点的识别,我们引入了无监督的处理方案。它基于迭代阈值分解(ITD)和数学形态学运算。由于进行了连续的图像处理,它可以显示所有发射点,并从数据库中消除大部分噪声。在15个光子发射数据库(10个真实案例和5个模拟案例)上测试了基于五种阈值方法的ITD方法。将光子发射区域的定位与专家识别进行比较,并使用物体一致性误差对估计质量进行量化。 (C)2015 SPIE和IS&T

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