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titleImage retrieval for identifying house plants
authors Kebapcı Hanife, Yanıkoğlu Berrin, Ünal, Gözde
keywords
abstractWe 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).
typeConference Paper
journalConference on Imaging and Printing in a Web 2.0 World; and Multimedia content Access - Algorithms and Systems IV, San Jose, CA
published year2010
serial2067
is_viewableyes
(Total records:1429)
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