Fractional differentiation for edge detection
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| Title: | Fractional differentiation for edge detection |
|---|---|
| Authors: | Mathieu, B.1, Melchior, P. melchior@lap.u-bordeaux.fr, Oustaloup, A.1, Ceyral, Ch.1 |
| Source: | Signal Processing. Nov2003, Vol. 83 Issue 11, p2421. 12p. |
| Subjects: | Image processing, Differential operators, Laplacian operator, Partial differential equations |
| Abstract: | In image processing, edge detection often makes use of integer-order differentiation operators, especially order 1 used by the gradient and order 2 by the Laplacian. This paper demonstrates how introducing an edge detector based on non-integer (fractional) differentiation can improve the criterion of thin detection, or detection selectivity in the case of parabolic luminance transitions, and the criterion of immunity to noise, which can be interpreted in term of robustness to noise in general. [Copyright &y& Elsevier] |
| Copyright of Signal Processing is the property of Elsevier B.V. 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 11001115 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Fractional differentiation for edge detection – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mathieu%2C+B%2E%22">Mathieu, B.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Melchior%2C+P%2E%22">Melchior, P.</searchLink><i> melchior@lap.u-bordeaux.fr</i><br /><searchLink fieldCode="AR" term="%22Oustaloup%2C+A%2E%22">Oustaloup, A.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ceyral%2C+Ch%2E%22">Ceyral, Ch.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Signal+Processing%22">Signal Processing</searchLink>. Nov2003, Vol. 83 Issue 11, p2421. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Differential+operators%22">Differential operators</searchLink><br /><searchLink fieldCode="DE" term="%22Laplacian+operator%22">Laplacian operator</searchLink><br /><searchLink fieldCode="DE" term="%22Partial+differential+equations%22">Partial differential equations</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In image processing, edge detection often makes use of integer-order differentiation operators, especially order 1 used by the gradient and order 2 by the Laplacian. This paper demonstrates how introducing an edge detector based on non-integer (fractional) differentiation can improve the criterion of thin detection, or detection selectivity in the case of parabolic luminance transitions, and the criterion of immunity to noise, which can be interpreted in term of robustness to noise in general. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Signal Processing is the property of Elsevier B.V. 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=11001115 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/S0165-1684(03)00194-4 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 2421 Subjects: – SubjectFull: Image processing Type: general – SubjectFull: Differential operators Type: general – SubjectFull: Laplacian operator Type: general – SubjectFull: Partial differential equations Type: general Titles: – TitleFull: Fractional differentiation for edge detection Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mathieu, B. – PersonEntity: Name: NameFull: Melchior, P. – PersonEntity: Name: NameFull: Oustaloup, A. – PersonEntity: Name: NameFull: Ceyral, Ch. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2003 Type: published Y: 2003 Identifiers: – Type: issn-print Value: 01651684 Numbering: – Type: volume Value: 83 – Type: issue Value: 11 Titles: – TitleFull: Signal Processing Type: main |
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