DocumentCode
2480932
Title
Affine invariant shape descriptors: The ICA-Fourier descriptor and the PCA-Fourier descriptor
Author
Mei, Ye ; Androutsos, Dimitrios
Author_Institution
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
In this paper, we propose two new affine invariant shape descriptors, the ICA-Fourier descriptor and the PCA-Fourier descriptor. We tested the descriptors by using them as features for shape based silhouette image retrieval. Experiments on a 1000 silhouette image database show promising retrieval rates of 95.41% and 93.63%, using the ICA-Fourier descriptor and the PCA-Fourier descriptor, respectively. The relationship between those two descriptors are also explained. The proposed PCA-Fourier descriptor is computationally more efficient than its ICA counterpart, while having comparable performance.
Keywords
Fourier transforms; affine transforms; feature extraction; image retrieval; independent component analysis; principal component analysis; ICA-Fourier descriptor; PCA-Fourier descriptor; affine invariant shape descriptor; image database; independent component analysis; principal component analysis; shape based silhouette image retrieval; Computer vision; Fourier transforms; Image databases; Image retrieval; Independent component analysis; Information retrieval; Object recognition; Shape; Testing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761381
Filename
4761381
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