Plant image retrieval using color and texture features

Hanife Kebapci; Berrin Yanikoglu; Gozde Unal

doi:10.1109/ISCIS.2009.5291857

Plant image retrieval using color and texture features

Hanife Kebapci^*
, Berrin Yanikoglu
, Gozde Unal

^*Bu çalışma için yazışmadan sorumlu yazar

Sabanci University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

13 Atıf (Scopus)

Özet

An application of content-based image retrieval is proposed for identifying plants, along with a preliminary implementation. The system takes a plant image as input and finds the matching plant from a plant image database and is intended to provide users a simple method to locate information about their house plants. Max-flow min-cut technique is used as the image segmentation method to extract the general structure of the plant. Various color and texture features extracted from the segmented plant region are used in matching images to the database. Results show that for 60% of the queries, the correct plant image is retrieved among the top-10 results, using a small database of 188 images.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
Sayfalar	82-87
Sayfa sayısı	6
DOI'lar	https://doi.org/10.1109/ISCIS.2009.5291857
Yayın durumu	Yayınlandı - 2009
Harici olarak yayınlandı	Evet
Etkinlik	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009 - Guzelyurt, Cyprus Süre: 14 Eyl 2009 → 16 Eyl 2009

Yayın serisi

Adı	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
Ülke/Bölge	Cyprus
Şehir	Guzelyurt
Periyot	14/09/09 → 16/09/09

Belgeye Erişim

10.1109/ISCIS.2009.5291857

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

@inproceedings{ac74ec948bda41a3a85ba6a37bad4a09,

title = "Plant image retrieval using color and texture features",

abstract = "An application of content-based image retrieval is proposed for identifying plants, along with a preliminary implementation. The system takes a plant image as input and finds the matching plant from a plant image database and is intended to provide users a simple method to locate information about their house plants. Max-flow min-cut technique is used as the image segmentation method to extract the general structure of the plant. Various color and texture features extracted from the segmented plant region are used in matching images to the database. Results show that for 60\% of the queries, the correct plant image is retrieved among the top-10 results, using a small database of 188 images.",

author = "Hanife Kebapci and Berrin Yanikoglu and Gozde Unal",

year = "2009",

doi = "10.1109/ISCIS.2009.5291857",

language = "English",

isbn = "9781424450237",

series = "2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009",

pages = "82--87",

booktitle = "2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009",

note = "2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009 ; Conference date: 14-09-2009 Through 16-09-2009",

}

Kebapci, H, Yanikoglu, B & Unal, G 2009, Plant image retrieval using color and texture features. in 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009., 5291857, 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009, pp. 82-87, 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009, Guzelyurt, Cyprus, 14/09/09. https://doi.org/10.1109/ISCIS.2009.5291857

Plant image retrieval using color and texture features. / Kebapci, Hanife; Yanikoglu, Berrin; Unal, Gozde.
2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009. 2009. p. 82-87 5291857 (2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Plant image retrieval using color and texture features

AU - Kebapci, Hanife

AU - Yanikoglu, Berrin

AU - Unal, Gozde

PY - 2009

Y1 - 2009

N2 - An application of content-based image retrieval is proposed for identifying plants, along with a preliminary implementation. The system takes a plant image as input and finds the matching plant from a plant image database and is intended to provide users a simple method to locate information about their house plants. Max-flow min-cut technique is used as the image segmentation method to extract the general structure of the plant. Various color and texture features extracted from the segmented plant region are used in matching images to the database. Results show that for 60% of the queries, the correct plant image is retrieved among the top-10 results, using a small database of 188 images.

AB - An application of content-based image retrieval is proposed for identifying plants, along with a preliminary implementation. The system takes a plant image as input and finds the matching plant from a plant image database and is intended to provide users a simple method to locate information about their house plants. Max-flow min-cut technique is used as the image segmentation method to extract the general structure of the plant. Various color and texture features extracted from the segmented plant region are used in matching images to the database. Results show that for 60% of the queries, the correct plant image is retrieved among the top-10 results, using a small database of 188 images.

UR - https://www.scopus.com/pages/publications/73949131001

U2 - 10.1109/ISCIS.2009.5291857

DO - 10.1109/ISCIS.2009.5291857

M3 - Conference contribution

AN - SCOPUS:73949131001

SN - 9781424450237

T3 - 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009

SP - 82

EP - 87

BT - 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009

T2 - 2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009

Y2 - 14 September 2009 through 16 September 2009

ER -

Plant image retrieval using color and texture features

Özet

Yayın serisi

???event.eventtypes.event.conference???

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

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