DC Field | Value | Language |
---|---|---|
dc.contributor.author | 유진규 | ko |
dc.contributor.author | 한송희 | ko |
dc.contributor.author | 이창옥 | ko |
dc.date.accessioned | 2023-01-05T09:01:04Z | - |
dc.date.available | 2023-01-05T09:01:04Z | - |
dc.date.created | 2023-01-05 | - |
dc.date.created | 2023-01-05 | - |
dc.date.created | 2023-01-05 | - |
dc.date.created | 2023-01-05 | - |
dc.date.issued | 2022-12 | - |
dc.identifier.citation | JOURNAL OF THE KOREAN SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS, v.26, no.4, pp.263 - 279 | - |
dc.identifier.issn | 1226-9433 | - |
dc.identifier.uri | http://hdl.handle.net/10203/304075 | - |
dc.description.abstract | This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods. | - |
dc.language | English | - |
dc.publisher | KOREAN SOC INDUSTRIAL & APPLIED MATHEMATICS | - |
dc.title | DEFECT INSPECTION IN SEMICONDUCTOR IMAGES USING HISTOGRAM FITTING AND NEURAL NETWORKS | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 26 | - |
dc.citation.issue | 4 | - |
dc.citation.beginningpage | 263 | - |
dc.citation.endingpage | 279 | - |
dc.citation.publicationname | JOURNAL OF THE KOREAN SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS | - |
dc.identifier.kciid | ART002907940 | - |
dc.contributor.localauthor | 이창옥 | - |
dc.contributor.nonIdAuthor | 한송희 | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordAuthor | Defect inspection | - |
dc.subject.keywordAuthor | semiconductor image | - |
dc.subject.keywordAuthor | double-fit method | - |
dc.subject.keywordAuthor | right singular vector | - |
dc.subject.keywordAuthor | neural networks. | - |
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