DocumentCode :
2314057
Title :
Edge potential functions and genetic algorithms for shape-based image retrieval
Author :
Dao, Minh-Son ; De Natale, Francesco G B ; Massa, Andrea
Author_Institution :
DIT, Trento Univ., Italy
Volume :
3
fYear :
2003
fDate :
14-17 Sept. 2003
Abstract :
In this paper, a new approach to the image retrieval problem is presented, that uses edge potential functions (EPF) and genetic algorithms (GA). The method allows a user to draw a rough sketch of the shape and to find or rank the images in a database that contain a similar shape at any position, rotation and scaling factor. It is explained how GAs allow to exploit the capability of EPFs to attract a sketch contour as a result, the algorithm provides the set of geometrical transformations corresponding to the best match, and a confidence factor about the presence of a matching object. The method has been widely tested achieving very satisfactory results.
Keywords :
genetic algorithms; image matching; image retrieval; visual databases; edge potential functions; genetic algorithms; geometrical transformations; image retrieval problem; object matching; Content based retrieval; Digital images; Genetic algorithms; IEEE members; IP networks; Image databases; Image retrieval; Shape measurement; Spatial databases; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-7750-8
Type :
conf
DOI :
10.1109/ICIP.2003.1247348
Filename :
1247348
Link To Document :
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