Please use this identifier to cite or link to this item:
Title: Fuzzy integral for leaf image retrieval
Authors: Wang, Z
Chi, Z 
Feng, D
Issue Date: 2002
Source: Proceedings of the 2002 IEEE International Conference on Fuzzy Systems, 2002 : FUZZ-IEEE'02, May 2002, Honolulu, HI, p. 372-377
Abstract: Generally, the more features utilized, the better the retrieval performance. However, it is a very challenging task to combine different feature sets in a way reflecting human perception. This paper presents the combination of different shape based feature sets using fuzzy integral for leaf image retrieval. The feature sets used in our system include centroid-contour distance curve, eccentricity, and angle code histogram. The fuzzy integral approach can release the user's burden from tuning the combination parameters. In order to reduce the matching time in the retrieval process, a thinning based method is proposed to locate the start point of a leaf contour. Experimental results on 440 leaf images from 44 plant species (10 samples from each plant species) show that the fuzzy integral approach can achieve a comparable retrieval performance with the best case of the weighted summation combination. The results also indicate that our approach, which are more efficient, can achieve a better retrieval performance than both the curvature scale space (CSS) method and the modified Fourier descriptor (MFD) method
Keywords: Biology computing
Fuzzy set theory
Image matching
Image retrieval
Publisher: IEEE
ISBN: 0-7803-7280-8
DOI: 10.1109/FUZZ.2002.1005019
Appears in Collections:Conference Paper

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

Page view(s)

Last Week
Last month
Citations as of Sep 16, 2020

Google ScholarTM



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