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Proceedings Article

Image retrieval for identifying house plants

[+] Author Affiliations
Hanife Kebapci, Berrin Yanikoglu, Gozde Unal

Sabanci Univ. (Turkey)

Proc. SPIE 7540, Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV, 754011 (February 10, 2010); doi:10.1117/12.839097
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From Conference Volume 7540

  • Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV
  • Qian Lin; Zhigang Z. Fan; Theo Gevers; Raimondo Schettini; Cees Snoek
  • San Jose, California | January 17, 2010

abstract

We present a content-based image retrieval system for plant identification which is intended for providing users with a simple method to locate information about their house plants. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various well-known color, texture and shape features for this problem, as well as introducing some new ones. The features are extracted from the general plant region that is segmented from the background using the max-flow min-cut technique. Results on a database of 132 different plant images show promise (in about 72% of the queries, the correct plant image is retrieved among the top-15 results).

© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Hanife Kebapci ; Berrin Yanikoglu and Gozde Unal
"Image retrieval for identifying house plants", Proc. SPIE 7540, Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV, 754011 (February 10, 2010); doi:10.1117/12.839097; http://dx.doi.org/10.1117/12.839097


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