6533b860fe1ef96bd12c31bb
RESEARCH PRODUCT
Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location
Sabir JacquirStéphane BinczakKevin SanchezPhilippe PerduSamuel Chefsubject
Computer scienceImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyIntegrated circuitIntegrated circuit design01 natural scienceslaw.inventionlaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic Engineering[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics010302 applied physicsSignal processingNoise (signal processing)business.industryPattern recognitionImage segmentationThresholdingAtomic and Molecular Physics and OpticsComputer Science ApplicationsCMOS[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingdescription
International audience; 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.
year | journal | country | edition | language |
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2015-01-27 |