@inproceedings{f40c1a2b75a14c479e7e3e96648a9c1d,
title = "Image retrieval for identifying house plants",
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).",
keywords = "Color features, Contour-based shape features, Gabor wavelets, Image retrieval, Sift",
author = "Hanife Kebapci and Berrin Yanikoglu and Gozde Unal",
year = "2010",
doi = "10.1117/12.839097",
language = "English",
isbn = "9780819479334",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Imaging and Printing in a Web 2.0 World; and Multimedia Content Access",
note = "Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV ; Conference date: 19-01-2010 Through 21-01-2010",
}