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dc.contributor.authorChen, X
dc.contributor.authorWang, B
dc.contributor.authorGao, Y
dc.date.accessioned2021-08-05T05:16:42Z
dc.date.available2021-08-05T05:16:42Z
dc.date.issued2020
dc.identifier.isbn9781728188089
dc.identifier.issn1051-4651
dc.identifier.doi10.1109/ICPR48806.2021.9412080
dc.identifier.urihttp://hdl.handle.net/10072/406622
dc.description.abstractIdentifying butterfly species by image patterns is a challenging task in computer vision and pattern recognition community due to many butterfly species having similar shape patterns with complex interior structures and considerable pose variation. In additional, geometrical transformation and illumination variation also make this task more difficult. In this paper, a novel image descriptor, named Gaussian convolution angle (GCA) is proposed for butterfly species classification. The proposed GCA projects the butterfly vein image function and intensity image function along a group of vectors that start from a common contour points and ends at the remaining contour points which results a group of vectors that capture the complex vein patterns and texture patterns of butterfly images. The Gaussian convolutions of different scales are conducted to the resulting vector functions to generate a multiscale GCA descriptors. The proposed GCA is not only invariant to geometrical transformation including rotation, scaling and translation, but also invariant to lighting change. The proposed method has been tested on a publicly available butterfly image dataset that has 832 samples of 10 species. It achieves a classification accuracy of 92.03% which is higher than the benchmark methods.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherIEEE/IEEE Computer Society
dc.relation.ispartofconferencename2020 25th International Conference on Pattern Recognition (ICPR)
dc.relation.ispartofconferencetitleProceedings of ICPR 2020 25th International Conference on Pattern Recognition
dc.relation.ispartofdatefrom2021-01-10
dc.relation.ispartofdateto2021-01-15
dc.relation.ispartoflocationMilan, Italy
dc.relation.ispartofpagefrom5798
dc.relation.ispartofpageto5803
dc.subject.fieldofresearchInformation systems
dc.subject.fieldofresearchcode4609
dc.titleGaussian convolution angles: Invariant vein and texture descriptors for butterfly species identification
dc.typeConference output
dc.type.descriptionE1 - Conferences
dcterms.bibliographicCitationChen, X; Wang, B; Gao, Y, Gaussian convolution angles: Invariant vein and texture descriptors for butterfly species identification, Proceedings of ICPR 2020 25th International Conference on Pattern Recognition, 2020, pp. 5798-5803
dc.date.updated2021-08-04T23:53:04Z
gro.hasfulltextNo Full Text
gro.griffith.authorGao, Yongsheng


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