Please use this identifier to cite or link to this item: https://doi.org/10.1007/s001380050133
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dc.titleGolden-template self-generating method for patterned wafer inspection
dc.contributor.authorXie, P.
dc.contributor.authorGuan, S.-U.
dc.date.accessioned2014-06-17T06:49:08Z
dc.date.available2014-06-17T06:49:08Z
dc.date.issued2000-10
dc.identifier.citationXie, P., Guan, S.-U. (2000-10). Golden-template self-generating method for patterned wafer inspection. Machine Vision and Applications 12 (3) : 149-156. ScholarBank@NUS Repository. https://doi.org/10.1007/s001380050133
dc.identifier.issn09328092
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/62262
dc.description.abstractThis paper presents a novel golden-template selfgenerating technique for detecting possible defects in periodic two-dimensional wafer images. A golden template of the patterned wafer image under inspection can be obtained from the wafer image itself and no other prior knowledge is needed. It is a bridge between the existing self-reference methods and image-to-image reference methods. Spectral estimation is used in the first step to derive the periods of repeating patterns in both directions. Then a building block representing the structure of the patterns is extracted using interpolation to obtain sub-pixel resolution. After that, a new defect-free golden template is built based on the extracted building block. Finally, a pixel-to-pixel comparison is all we need to find possible defects. A comparison between the results of the proposed method and those of the previously published methods is presented.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s001380050133
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1007/s001380050133
dc.description.sourcetitleMachine Vision and Applications
dc.description.volume12
dc.description.issue3
dc.description.page149-156
dc.description.codenMVAPE
dc.identifier.isiut000089927000005
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