Feasibility of computer-aided identification of foraminiferal tests
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| Title: | Feasibility of computer-aided identification of foraminiferal tests |
|---|---|
| Authors: | Ranaweera, Kamal1, Harrison, Adam P.1, Bains, Santo2, Joseph, Dileepan1 dil.joseph@ualberta.ca |
| Source: | Marine Micropaleontology. Jun2009, Vol. 72 Issue 1/2, p66-75. 10p. |
| Subjects: | Automatic identification, Microscopy, Foraminifera, Electronic data interchange |
| Abstract: | Abstract: Over the past two decades, several investigators have worked on computerized systems to accelerate the identification of foraminiferal tests (forams). Leading examples have focused on fully-automatic identification using neural networks and supervised learning. This paper introduces an alternative semi-automatic or computer-aided approach. Such an approach reduces the workload associated with foram identification without the challenges of training set collection and fully-automatic recognition. The proposed method begins by photographing a collection of specimens sprinkled on a microscopy slide. Segmented images are then mapped into a canonical space where position, rotation, and scale are normalized. Specimens are clustered based on image similarity in the canonical space. A specialist then identifies the clusters by inspecting representative templates. Experimental results show that the identification effort can be reduced by 35%, yet the accuracy remains comparable to when every specimen is individually identified. Further reduction of effort was prevented by the significant variability of illumination direction in the canonical images. These results encourage further work on a computer-aided approach to foram identification. [Copyright &y& Elsevier] |
| Copyright of Marine Micropaleontology 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: 40634250 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Feasibility of computer-aided identification of foraminiferal tests – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ranaweera%2C+Kamal%22">Ranaweera, Kamal</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Harrison%2C+Adam+P%2E%22">Harrison, Adam P.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bains%2C+Santo%22">Bains, Santo</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Joseph%2C+Dileepan%22">Joseph, Dileepan</searchLink><relatesTo>1</relatesTo><i> dil.joseph@ualberta.ca</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Marine+Micropaleontology%22">Marine Micropaleontology</searchLink>. Jun2009, Vol. 72 Issue 1/2, p66-75. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Automatic+identification%22">Automatic identification</searchLink><br /><searchLink fieldCode="DE" term="%22Microscopy%22">Microscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Foraminifera%22">Foraminifera</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+interchange%22">Electronic data interchange</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: Over the past two decades, several investigators have worked on computerized systems to accelerate the identification of foraminiferal tests (forams). Leading examples have focused on fully-automatic identification using neural networks and supervised learning. This paper introduces an alternative semi-automatic or computer-aided approach. Such an approach reduces the workload associated with foram identification without the challenges of training set collection and fully-automatic recognition. The proposed method begins by photographing a collection of specimens sprinkled on a microscopy slide. Segmented images are then mapped into a canonical space where position, rotation, and scale are normalized. Specimens are clustered based on image similarity in the canonical space. A specialist then identifies the clusters by inspecting representative templates. Experimental results show that the identification effort can be reduced by 35%, yet the accuracy remains comparable to when every specimen is individually identified. Further reduction of effort was prevented by the significant variability of illumination direction in the canonical images. These results encourage further work on a computer-aided approach to foram identification. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Marine Micropaleontology 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.marmicro.2009.03.005 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 66 Subjects: – SubjectFull: Automatic identification Type: general – SubjectFull: Microscopy Type: general – SubjectFull: Foraminifera Type: general – SubjectFull: Electronic data interchange Type: general Titles: – TitleFull: Feasibility of computer-aided identification of foraminiferal tests Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ranaweera, Kamal – PersonEntity: Name: NameFull: Harrison, Adam P. – PersonEntity: Name: NameFull: Bains, Santo – PersonEntity: Name: NameFull: Joseph, Dileepan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 03778398 Numbering: – Type: volume Value: 72 – Type: issue Value: 1/2 Titles: – TitleFull: Marine Micropaleontology Type: main |
| ResultId | 1 |
