Presentation 2006-03-16
Recognition Method of Minute Defect Based on Statistical Outlier Detection using Plural Pattern Images
Kaoru SAKAI, Shunji MAEDA,
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Abstract(in English) Reductions of the pattern variation noise caused by the manufacturing process are essential to recognize a minute defect on the complicated multilayer patterns of semiconductor wafers. We propose a highly sensitive comparison inspection method with noise reduction. We control the scattergram data of images by using plural images and we recognize the minute defect as an outlier. This new method can detect small defects that exceed the resolution limit in optics.
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Keyword(in English) Comparison inspection / Defect recognition / Statistical outlier detection
Paper # PRMU2005-233
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Conference Information
Committee PRMU
Conference Date 2006/3/9(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Recognition Method of Minute Defect Based on Statistical Outlier Detection using Plural Pattern Images
Sub Title (in English)
Keyword(1) Comparison inspection
Keyword(2) Defect recognition
Keyword(3) Statistical outlier detection
1st Author's Name Kaoru SAKAI
1st Author's Affiliation Hitachi,LTD., Production Engineering Research Laboratory()
2nd Author's Name Shunji MAEDA
2nd Author's Affiliation Hitachi,LTD., Production Engineering Research Laboratory
Date 2006-03-16
Paper # PRMU2005-233
Volume (vol) vol.105
Number (no) 673
Page pp.pp.-
#Pages 6
Date of Issue