Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17399
Title: Leaf image retrieval using combined shape feature sets with fuzzy integral
Authors: Wang, Z
Chi, Z 
Feng, D
Keywords: Angle code histogram
Centroid-contour distance
Fuzzy integral
Image retrieval
Leaf image processing
Moment invariants
Shape features
Issue Date: 2003
Publisher: Technology Exchange Limited Hong Kong
Source: Chinese journal of electronics, 2003, v. 12, no. 4, p. 572-578 How to cite?
Journal: Chinese Journal of Electronics 
Abstract: In this paper, leaf image retrieval using combined three shape feature sets is presented. The shape feature sets adopted include Centroid-contour distance (CCD) curve, Moment invariants (MIs), and Angle code histogram (ACH). At first, a thinning-based method is proposed to locate possible starting points of a leaf image contour so that the approach is more computationally efficient in image matching. This starting point location method can also benefit other shape representation schemes that are sensitive to starting points. After the similarity measures of individual feature sets are computed, a fuzzy integral is employed to combine them. The fuzzy integral approach has a distinct advantage in releasing the user's burden from tuning the combination parameters required in the weighted summation approach that is time-consuming and cannot guarantee the best combination performance. Experimental results on our 830 leaf images from 83 plants (10 samples from each plant) show that our approach compared favorably with other two methods tested, the Curvature scale space (CSS) method and the Modified fourier descriptor (MFD) method.
URI: http://hdl.handle.net/10397/17399
ISSN: 1022-4653
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