DocumentCode :
1743083
Title :
Statistical shape features in content-based image retrieval
Author :
Brandt, Sami ; Laaksonen, Jorma ; Oja, Erkki
Author_Institution :
Lab. of Comput. Eng., Helsinki Univ. of Technol., Espoo, Finland
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
1062
Abstract :
In this article the use of shape features in content-based image retrieval is studied. The emphasis is on techniques which do not demand object segmentation. PicSOM, the image retrieval system used in the experiments, requires that features are represented by constant-sized feature vectors for which the Euclidean distance can be used as a similarity measure. The shape features suggested here are edge histograms and Fourier transform based features computed for an edge image in Cartesian and polar coordinate planes. The results show that both local and global shape features are important clues of shapes in an image
Keywords :
Fourier transforms; edge detection; feature extraction; image retrieval; search engines; statistical analysis; visual databases; Euclidean distance; Fourier transform; PicSOM; content-based image retrieval; edge detection; edge histograms; feature vectors; image database; search engine; statistical shape features; Content based retrieval; Feature extraction; Histograms; Image databases; Image retrieval; Image segmentation; Laboratories; Search engines; Shape; 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.2000.906258
Filename :
906258
Link To Document :
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