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

^*Corresponding author for this work

Sabanci University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

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.

Original language	English
Title of host publication	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
Pages	82-87
Number of pages	6
DOIs	https://doi.org/10.1109/ISCIS.2009.5291857
Publication status	Published - 2009
Externally published	Yes
Event	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009 - Guzelyurt, Cyprus Duration: 14 Sept 2009 → 16 Sept 2009

Publication series

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

Conference

Conference	2009 24th International Symposium on Computer and Information Sciences, ISCIS 2009
Country/Territory	Cyprus
City	Guzelyurt
Period	14/09/09 → 16/09/09

Access to Document

10.1109/ISCIS.2009.5291857

Cite this

@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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

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DO - 10.1109/ISCIS.2009.5291857

M3 - Conference contribution

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SN - 9781424450237

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

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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

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