| A flower image retrieval method based on ROI feature. | |
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MedLine Citation:
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PMID: 15495304 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999). |
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Authors:
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An-Xiang Hong; Gang Chen; Jun-Li Li; Zhe-Ru Chi; Dan Zhang |
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Publication Detail:
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Type: Comparative Study; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies |
Journal Detail:
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Title: Journal of Zhejiang University. Science Volume: 5 ISSN: 1009-3095 ISO Abbreviation: J. Zhejiang Univ. Sci. Publication Date: 2004 Jul |
Date Detail:
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Created Date: 2004-10-20 Completed Date: 2005-03-08 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 100954270 Medline TA: J Zhejiang Univ Sci Country: China |
Other Details:
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Languages: eng Pagination: 764-72 Citation Subset: IM |
Affiliation:
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Department of Applied Mathematics, Zhejiang University, Hangzhou 310027, China. Hax@nbit.gov.cn |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Artificial Intelligence Cluster Analysis Color Colorimetry / methods* Flowers / anatomy & histology*, classification* Image Enhancement / methods Image Interpretation, Computer-Assisted / methods* Information Storage and Retrieval / methods Numerical Analysis, Computer-Assisted Pattern Recognition, Automated / methods* Photography / methods* Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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