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

Samuel Chef; Sabir Jacquir; Kevin Sanchez; Philippe Perdu; Stéphane Binczak

doi:10.1117/1.JEI.24.1.013019

27 January 2015 Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location

Samuel Chef, Sabir Jacquir, Kevin Sanchez, Philippe Perdu, Stéphane Binczak

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 1, 013019 (January 2015). https://doi.org/10.1117/1.JEI.24.1.013019

Abstract

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.

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Samuel Chef, Sabir Jacquir, Kevin Sanchez, Philippe Perdu, and Stéphane Binczak "Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location," Journal of Electronic Imaging 24(1), 013019 (27 January 2015). https://doi.org/10.1117/1.JEI.24.1.013019

Published: 27 January 2015

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