Share Email Print
cover

Proceedings Paper

Image retrieval for identifying house plants
Author(s): Hanife Kebapci; Berrin Yanikoglu; Gozde Unal
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper 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).

Paper Details

Date Published: 10 February 2010
PDF: 8 pages
Proc. SPIE 7540, Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV, 754011 (10 February 2010); doi: 10.1117/12.839097
Show Author Affiliations
Hanife Kebapci, Sabanci Univ. (Turkey)
Berrin Yanikoglu, Sabanci Univ. (Turkey)
Gozde Unal, Sabanci Univ. (Turkey)


Published in SPIE Proceedings Vol. 7540:
Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV
Theo Gevers; Raimondo Schettini; Cees Snoek; Qian Lin; Zhigang Fan, Editor(s)

© SPIE. Terms of Use
Back to Top