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Conference Paper: Graylevel alignment between two images using linear programming

TitleGraylevel alignment between two images using linear programming
Authors
KeywordsComputers
Computer graphics
Issue Date2003
PublisherIEEE.
Citation
Ieee International Conference On Image Processing, 2003, v. 2, p. 327-330 How to Cite?
AbstractA critical step in defect detection for semiconductor process is to align a test image against a reference. This includes both spatial alignment and grayscale alignment. For the latter, a direct least square approach is not very applicable because the presence of defects would skew the parameters. Instead, we use a linear programming formulation which has the advantage of having a fast algorithm, while at the same time can produce better alignment of the test image to the reference. Furthermore, this is a flexible algorithm capable of incorporating additional constraints, such as ensuring that the aligned pixel values are within the allowable intensity range.
Persistent Identifierhttp://hdl.handle.net/10722/46405
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorLam, EYen_HK
dc.date.accessioned2007-10-30T06:49:10Z-
dc.date.available2007-10-30T06:49:10Z-
dc.date.issued2003en_HK
dc.identifier.citationIeee International Conference On Image Processing, 2003, v. 2, p. 327-330en_HK
dc.identifier.issn1522-4880en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46405-
dc.description.abstractA critical step in defect detection for semiconductor process is to align a test image against a reference. This includes both spatial alignment and grayscale alignment. For the latter, a direct least square approach is not very applicable because the presence of defects would skew the parameters. Instead, we use a linear programming formulation which has the advantage of having a fast algorithm, while at the same time can produce better alignment of the test image to the reference. Furthermore, this is a flexible algorithm capable of incorporating additional constraints, such as ensuring that the aligned pixel values are within the allowable intensity range.en_HK
dc.format.extent296143 bytes-
dc.format.extent4084 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE International Conference on Image Processingen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectComputersen_HK
dc.subjectComputer graphicsen_HK
dc.titleGraylevel alignment between two images using linear programmingen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1522-4880&volume=2&spage=327&epage=330&date=2003&atitle=Graylevel+alignment+between+two+images+using+linear+programmingen_HK
dc.identifier.emailLam, EY:elam@eee.hku.hken_HK
dc.identifier.authorityLam, EY=rp00131en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICIP.2003.1246683en_HK
dc.identifier.scopuseid_2-s2.0-0344704004en_HK
dc.identifier.hkuros88832-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0344704004&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2en_HK
dc.identifier.spage327en_HK
dc.identifier.epage330en_HK
dc.identifier.scopusauthoridLam, EY=7102890004en_HK

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