Please use this identifier to cite or link to this item:
|Title:||A golden-block-based self-refining scheme for repetitive patterned wafer inspections||Authors:||Guan, S.-U.
Image-to-image reference method
|Issue Date:||Mar-2003||Citation:||Guan, S.-U., Xie, P., Li, H. (2003-03). A golden-block-based self-refining scheme for repetitive patterned wafer inspections. Machine Vision and Applications 13 (5-6) : 314-321. ScholarBank@NUS Repository. https://doi.org/10.1007/s00138-002-0086-x||Abstract:||This paper presents a novel technique for detecting possible defects in two-dimensional wafer images with repetitive patterns using prior knowledge. The technique has a learning ability that can create a golden-block database from the wafer image itself, then modify and refine its content when used in further inspections. The extracted building block is stored as a golden block for the detected pattern. When new wafer images with the same periodical pattern arrive, we do not have to recalculate their periods and building blocks. A new building block can be derived directly from the existing golden block after eliminating alignment differences. If the newly derived building block has better quality than the stored golden block, then the golden block is replaced with the new building block. With the proposed algorithm, our implementation shows that a significant amount of processing time is saved. Also, the storage overhead of golden templates is reduced significantly by storing golden blocks only.||Source Title:||Machine Vision and Applications||URI:||http://scholarbank.nus.edu.sg/handle/10635/54224||ISSN:||09328092||DOI:||10.1007/s00138-002-0086-x|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Mar 27, 2020
WEB OF SCIENCETM
checked on Mar 20, 2020
checked on Mar 31, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.