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
Este artigo descreve um método de detecção de defeitos que extrai automaticamente informações de defeitos de padrões LSI de fundo complicados. Com base em uma imagem de microscópio eletrônico de varredura (MEV), os defeitos no wafer são caracterizados em termos de localização, tamanho e formato dos defeitos. Para tanto, duas técnicas de processamento de imagens, a transformada de Hough e a transformada wavelet, foram empregadas. Especialmente, a Transformada de Hough para círculos é aplicada a defeitos não circulares para estimar as formas dos defeitos. Através de experiências, foi demonstrado que o sistema é muito eficaz na identificação de defeitos e será utilizado como parte integrante em futuros sistemas automáticos de classificação de padrões de defeitos.
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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 -