Automatic plant identification from photographs

dc.authorid Aptoula, Erchan/0000-0001-6168-2883
dc.authorid Yanikoglu, Berrin/0000-0001-7403-7592
dc.authorscopusid 35617171700
dc.authorscopusid 23396161700
dc.authorscopusid 35103743700
dc.authorwosid Aptoula, Erchan/AAI-1070-2020
dc.authorwosid Yanikoglu, Berrin/AAE-4843-2022
dc.contributor.author Yanikoglu, B.
dc.contributor.author Aptoula, E.
dc.contributor.author Tirkaz, C.
dc.date.accessioned 2024-05-25T11:23:32Z
dc.date.available 2024-05-25T11:23:32Z
dc.date.issued 2014
dc.department Okan University en_US
dc.department-temp [Yanikoglu, B.; Tirkaz, C.] Sabanci Univ, TR-34956 Istanbul, Turkey; [Aptoula, E.] Okan Univ, TR-34959 Istanbul, Turkey en_US
dc.description Aptoula, Erchan/0000-0001-6168-2883; Yanikoglu, Berrin/0000-0001-7403-7592 en_US
dc.description.abstract We present a plant identification system for automatically identifying the plant in a given image. In addition to common difficulties faced in object recognition, such as light, pose and orientation variations, there are further difficulties particular to this problem, such as changing leaf shapes according to plant age and changes in the overall shape due to leaf composition. Our system uses a rich variety of shape, texture and color features, some being specific to the plant domain. The system has achieved the best overall score in the ImageCLEF'12 plant identification campaign in both the automatic and human-assisted categories. We report the results of this system on the publicly available ImageCLEF' 12 plant dataset, as well as the effectiveness of individual features. The results show 61 and 81 % accuracies in classifying the 126 different plant species in the top-1 and top-5 choices. en_US
dc.identifier.citationcount 65
dc.identifier.doi 10.1007/s00138-014-0612-7
dc.identifier.endpage 1383 en_US
dc.identifier.issn 0932-8092
dc.identifier.issn 1432-1769
dc.identifier.issue 6 en_US
dc.identifier.scopus 2-s2.0-84904468634
dc.identifier.scopusquality Q2
dc.identifier.startpage 1369 en_US
dc.identifier.uri https://doi.org/10.1007/s00138-014-0612-7
dc.identifier.uri https://hdl.handle.net/20.500.14517/738
dc.identifier.volume 25 en_US
dc.identifier.wos WOS:000342435400001
dc.identifier.wosquality Q2
dc.language.iso en
dc.publisher Springer en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 79
dc.subject Plant identification en_US
dc.subject Leaf shape en_US
dc.subject Color image segmentation en_US
dc.subject Mathematical morphology en_US
dc.title Automatic plant identification from photographs en_US
dc.type Article en_US
dc.wos.citedbyCount 64

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