The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article décrit une méthode de détection de défauts qui extrait automatiquement les informations sur les défauts à partir de modèles LSI d'arrière-plan complexes. Sur la base d'une image au microscope électronique à balayage (MEB), les défauts sur la plaquette sont caractérisés en termes d'emplacement, de taille et de forme des défauts. Pour cela, deux techniques de traitement d'image, la transformée de Hough et la transformée en ondelettes, ont été utilisées. En particulier, la transformée de Hough pour les cercles est appliquée aux défauts non circulaires pour estimer la forme des défauts. Des expériences ont démontré que le système est très efficace pour l'identification des défauts et qu'il fera partie intégrante des futurs systèmes de classification automatique des types de défauts.
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Kazuyuki MARUO, Tadashi SHIBATA, Takahiro YAMAGUCHI, Masayoshi ICHIKAWA, Tadahiro OHMI, "Automatic Defect Pattern Detection on LSI Wafers Using Image Processing Techniques" in IEICE TRANSACTIONS on Electronics,
vol. E82-C, no. 6, pp. 1003-1012, June 1999, doi: .
Abstract: This paper describes a defect detection method which automatically extracts defect information from complicated background LSI patterns. Based on a scanning electron microscope (SEM) image, the defects on the wafer are characterized in terms of their locations, sizes and the shape of defects. For this purpose, two image processing techniques, the Hough transform and wavelet transform, have been employed. Especially, the Hough Transform for circles is applied to non-circular defects for estimating the shapes of defects. By experiments, it has been demonstrated that the system is very effective in defect identification and will be used as an integral part in future automatic defect pattern classification systems.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e82-c_6_1003/_p
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@ARTICLE{e82-c_6_1003,
author={Kazuyuki MARUO, Tadashi SHIBATA, Takahiro YAMAGUCHI, Masayoshi ICHIKAWA, Tadahiro OHMI, },
journal={IEICE TRANSACTIONS on Electronics},
title={Automatic Defect Pattern Detection on LSI Wafers Using Image Processing Techniques},
year={1999},
volume={E82-C},
number={6},
pages={1003-1012},
abstract={This paper describes a defect detection method which automatically extracts defect information from complicated background LSI patterns. Based on a scanning electron microscope (SEM) image, the defects on the wafer are characterized in terms of their locations, sizes and the shape of defects. For this purpose, two image processing techniques, the Hough transform and wavelet transform, have been employed. Especially, the Hough Transform for circles is applied to non-circular defects for estimating the shapes of defects. By experiments, it has been demonstrated that the system is very effective in defect identification and will be used as an integral part in future automatic defect pattern classification systems.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Automatic Defect Pattern Detection on LSI Wafers Using Image Processing Techniques
T2 - IEICE TRANSACTIONS on Electronics
SP - 1003
EP - 1012
AU - Kazuyuki MARUO
AU - Tadashi SHIBATA
AU - Takahiro YAMAGUCHI
AU - Masayoshi ICHIKAWA
AU - Tadahiro OHMI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E82-C
IS - 6
JA - IEICE TRANSACTIONS on Electronics
Y1 - June 1999
AB - This paper describes a defect detection method which automatically extracts defect information from complicated background LSI patterns. Based on a scanning electron microscope (SEM) image, the defects on the wafer are characterized in terms of their locations, sizes and the shape of defects. For this purpose, two image processing techniques, the Hough transform and wavelet transform, have been employed. Especially, the Hough Transform for circles is applied to non-circular defects for estimating the shapes of defects. By experiments, it has been demonstrated that the system is very effective in defect identification and will be used as an integral part in future automatic defect pattern classification systems.
ER -