Publication: Automation of Visual Inspection of Photomasks for Microelectronic Products
| creativeworkseries.issn | 2079-3537 | |
| dc.contributor.author | Khodataeva, T. S. | |
| dc.date.accessioned | 2024-12-28T14:07:58Z | |
| dc.date.available | 2024-12-28T14:07:58Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The choice of a specific research topic was caused by a request for the development and implementation of automatic optical inspection at a semiconductor plant. The purpose of the work was to develop requirements, conduct technical design and create an optical control system for geometry deviations from a photomask drawing and a conductive pattern obtained using a manual stencil printer using relatively inexpensive equipment. As a result of the research, a pilot design sample of an automated optical control system using relatively inexpensive equipment was created and a computational algorithm was developed that ensures increased performance of the visual image recognition system, which allows to significantly reduce the percentage of defects. The work describes the implemented algorithm for obtaining images by an optical system and extracting images from a drawing file. Regardless of the method of obtaining an image (optical system, scanning electron microscope), there remains interest in choosing a criterion for comparing the obtained image with the reference one. The paper studies quantitative empirical metrics - Mean Square Error and Peak Signal-to-Noise Ratio for various noise reduction methods Block-Matching and 3D filtering and the classical spatial filtering method of Gaussian blur. The sensitivity of the structural similarity index metric to structural distortions of images after noise reduction is checked, taking into account the minimum values of the structural elements of metal-ceramic housings. Based on the Rosner test applied to the obtained values of the structural similarity metric, images containing defects are identified. The user interface provides for the output of the image area with a defect to the operator's screen. | |
| dc.identifier.citation | T.S. Khodataeva. Automation of Visual Inspection of Photomasks for Microelectronic Products (2024). Scientific Visualization 16.5: 86 - 97, DOI: 10.26583/sv.16.5.06 | |
| dc.identifier.doi | 10.26583/sv.16.5.06 | |
| dc.identifier.uri | https://openrepository.mephi.ru/handle/123456789/30287 | |
| dc.identifier.uri | http://sv-journal.org/2024-5/06/ | |
| dc.publisher | НИЯУ МИФИ | |
| dc.subject | Integrated circuit | |
| dc.subject | Visual analysis | |
| dc.subject | Photomask | |
| dc.subject | Drawing geometry | |
| dc.subject | Image processing | |
| dc.subject | Visualization | |
| dc.subject | Computer vision | |
| dc.title | Automation of Visual Inspection of Photomasks for Microelectronic Products | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| journal.title | Научная визуализация | |
| journalvolume.identifier.name | Научная визуализация | |
| relation.isJournalIssueOfPublication | a0dcd0b8-918a-4636-889b-a38462fef449 | |
| relation.isJournalIssueOfPublication.latestForDiscovery | a0dcd0b8-918a-4636-889b-a38462fef449 | |
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