Defect detection in periodic patterns using a multi-band-pass filter.
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| Title: | Defect detection in periodic patterns using a multi-band-pass filter. |
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| Authors: | Tsai, Zong-Da zdtsai@msn.com, Perng, Ming-Hwei1 |
| Source: | Machine Vision & Applications. Apr2013, Vol. 24 Issue 3, p551-565. 15p. 8 Black and White Photographs, 1 Diagram, 7 Charts, 1 Graph. |
| Subjects: | Image processing, Optical quality control, Automation, Mathematical convolutions, Filters (Mathematics) |
| Abstract: | This study presents a rapid and reliable technique for the inspection of defects in a two-dimensional periodic image using a multi-band-pass filter. More importantly, the blurring effect of the resultant defect images is significantly reduced, thereby resulting in a more precise estimation of the size of defects when compared with methods that use low-pass filtering. As a filter-based approach, the present technique does not require an alignment procedure. In addition, computational time is reduced by implementing multi-band-pass filters with convolution masks when the filters are operated in the spatial domain. Further, this approach involves mostly addition operations with very few multiplications; hence, computational time is significantly reduced when compared with those for existing approaches. The efficiency and effectiveness of the proposed multi-band-pass filter is verified through examples. It is observed that there is a significant reduction in blurring effects, leakage effects, and computational effort. It is noteworthy that though the proposed approach is presented as a two-dimensional filtering problem, it can be reduced to a one-dimensional filtering problem under the assumption that the misorientation angle of the inspected periodic pattern is negligibly small. [ABSTRACT FROM AUTHOR] |
| Copyright of Machine Vision & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 86051774 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Defect detection in periodic patterns using a multi-band-pass filter. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tsai%2C+Zong-Da%22">Tsai, Zong-Da</searchLink><i> zdtsai@msn.com</i><br /><searchLink fieldCode="AR" term="%22Perng%2C+Ming-Hwei%22">Perng, Ming-Hwei</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Machine+Vision+%26+Applications%22">Machine Vision & Applications</searchLink>. Apr2013, Vol. 24 Issue 3, p551-565. 15p. 8 Black and White Photographs, 1 Diagram, 7 Charts, 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+quality+control%22">Optical quality control</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+convolutions%22">Mathematical convolutions</searchLink><br /><searchLink fieldCode="DE" term="%22Filters+%28Mathematics%29%22">Filters (Mathematics)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study presents a rapid and reliable technique for the inspection of defects in a two-dimensional periodic image using a multi-band-pass filter. More importantly, the blurring effect of the resultant defect images is significantly reduced, thereby resulting in a more precise estimation of the size of defects when compared with methods that use low-pass filtering. As a filter-based approach, the present technique does not require an alignment procedure. In addition, computational time is reduced by implementing multi-band-pass filters with convolution masks when the filters are operated in the spatial domain. Further, this approach involves mostly addition operations with very few multiplications; hence, computational time is significantly reduced when compared with those for existing approaches. The efficiency and effectiveness of the proposed multi-band-pass filter is verified through examples. It is observed that there is a significant reduction in blurring effects, leakage effects, and computational effort. It is noteworthy that though the proposed approach is presented as a two-dimensional filtering problem, it can be reduced to a one-dimensional filtering problem under the assumption that the misorientation angle of the inspected periodic pattern is negligibly small. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Machine Vision & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00138-012-0425-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 551 Subjects: – SubjectFull: Image processing Type: general – SubjectFull: Optical quality control Type: general – SubjectFull: Automation Type: general – SubjectFull: Mathematical convolutions Type: general – SubjectFull: Filters (Mathematics) Type: general Titles: – TitleFull: Defect detection in periodic patterns using a multi-band-pass filter. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tsai, Zong-Da – PersonEntity: Name: NameFull: Perng, Ming-Hwei IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 09328092 Numbering: – Type: volume Value: 24 – Type: issue Value: 3 Titles: – TitleFull: Machine Vision & Applications Type: main |
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