Kebapcı, Hanife and Yanıkoğlu, Berrin and Ünal, Gözde (2010) Image retrieval for identifying house plants. In: Conference on Imaging and Printing in a Web 2.0 World; and Multimedia content Access - Algorithms and Systems IV, San Jose, CA
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Official URL: http://dx.doi.org/10.1117/12.839097
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).
Item Type: | Papers in Conference Proceedings |
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Uncontrolled Keywords: | image retrieval; color features; gabor wavelets; contour-based shape features; sift |
Subjects: | Q Science > Q Science (General) |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng. Faculty of Engineering and Natural Sciences > Academic programs > Electronics Faculty of Engineering and Natural Sciences |
Depositing User: | Berrin Yanıkoğlu |
Date Deposited: | 06 Dec 2010 11:21 |
Last Modified: | 26 Apr 2022 09:00 |
URI: | https://research.sabanciuniv.edu/id/eprint/16091 |