DocumentCode :
1742875
Title :
Color image retrieval using shape and spatial properties
Author :
Hsieh, Ing-sheen ; Fan, Kuo-Chin
Author_Institution :
Inst. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chung-Li, Taiwan
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
1023
Abstract :
In this paper, we present a novel region-based color image retrieval system using geometric properties. A region-growing technique is firstly employed to cluster the connected color pixels with the same color in an image to form color regions. Then, two most important descriptive geometry features are extracted. One is the spatial relational graph (SRG), another is the Fourier description coefficients (FDC) of each color region. In the matching stage, the modified relational distance graph matching between two SRG is performed firstly to find the best matches with the minimum relational distance. Then, the shape matching is applied to obtain the best vertex match with the minimum geometric distance. Experimental results reveal the feasibility of our proposed approach in solving color image retrieval problem
Keywords :
Fourier analysis; feature extraction; image colour analysis; image retrieval; relational algebra; FDC; Fourier description coefficients; SRG; best vertex match; color regions; connected color pixel clustering; descriptive geometry features; geometric properties; minimum geometric distance; minimum relational distance; modified relational distance graph matching; region-based color image retrieval system; region-growing technique; shape properties; spatial properties; spatial relational graph; Color; Computer science; Feature extraction; Image databases; Image matching; Image retrieval; Information retrieval; Pixel; Shape measurement; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.905645
Filename :
905645
Link To Document :
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