Please use this identifier to cite or link to this item:
Title: Flower image retrieval method based on ROI feature
Authors: Hong, AX
Chen, G
Li, JL
Chi, ZR 
Zhang, D
Keywords: Color features
Flower image characterization
Flower image retrieval
Knowledge-driven segmentation
Region-of-Interest (ROI)
Shape features
Issue Date: 2004
Publisher: Zhejiang University Press
Source: Journal of Zhejiang University. Science A, 2004, v. 5, no. 7, p. 764-772 How to cite?
Journal: Journal of Zhejiang University. Science A 
Abstract: Flower image retrieval is a very important step for computer-aided plant species recognition. 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 show 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 show 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).
ISSN: 1673-565X
EISSN: 1862-1775
DOI: 10.1631/jzus.2004.0764
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Feb 16, 2019

Page view(s)

Last Week
Last month
Citations as of Feb 18, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.