Database retrieval for similar images using ICA and PCA bases

Engineering Applications of Artificial Intelligence

Volumn 18, Issue 6, 2005, Pages 705-717

  Katsumata, Naoto ^a   Matsuyama, Yasuo ^a  

^a WASEDA UNIVERSITY   (Japan)

Author keywords

ICA; Image bases; Independent component analysis; PCA; Principal component analysis; Similar image retrieval

Indexed keywords

DATA PROCESSING; IMAGE PROCESSING; INDEPENDENT COMPONENT ANALYSIS; INFORMATION ANALYSIS; LOW PASS FILTERS; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL METHODS; WAVELET TRANSFORMS;

COLUMN VECTORS; HISTOGRAMS; IMAGES BASES; SIMILAR IMAGE RETRIEVAL;

IMAGE RETRIEVAL;

EID: 20144367740     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2005.01.002     Document Type: Article

References (15)

1. A.J. Bell, and T.J. Sejnowsiki An information maximization approach to blind separation and blind deconvolution Neural Computation 7 1995 1129 1159
2. A.J. Bell, and T.J. Sejnowsiki Edges are the 'Independent Components' of natural scenes Advances in Neural Information Processing Systems 9 1996 831 837
3. Cardoso, J.-F., Souloumiac, A., 1993. Blind beamforming for non Gaussian signals. IEE Proceedings F, vol. 140, pp. 362-370.
4. A. Deb Multimedia Systems and Content-Based Image Retrieval 2004 Idea Group Publishing Hershey, PA
5. Ground Truth Dababase, 1999. Object and Concept Recognition for Content-Based Image Retrieval Project, by L.G. Shapiro, University of Washington, Department of Computer Science and Engineering, http://www.cs. washington.edu/research/imagedatabase/groundtruth/.
6. P.O. Hoyer, and A. Hyvärinen Independent component analysis applied to feature extraction from colour and stereo image Network: Computation in Neural Systems 11 2000 191 210
7. A. Hyvärinen Fast and robust fixed-point algorithms for independent component analysis IEEE. Transactions on Neural Networks 10 1999 626 639
8. Hyvärinen, A., 2003. Extensions of ICA as models of natural image and visual processing. Proceedings of the International Symposium on ICA and BSS, pp. 963-974.
9. T.-S. Lee Image representation using 2D Gabor wavelets IEEE Transactions on Pattern Analysis and Machine Intelligence 18 1996 959 971
10. M.S. Lewicki, and B.A. Olshausen A probabilistic framework for adaptation and comparison of image codes Journal of the Optical Society of America 16 1999 1587 1601
11. Matsuyama, Y., Katsumata, N., Suzuki, Y., Imahara, S., 2000. The α -ICA algorithm. Proceedings of the International Workshop of Independent Component Analysis, pp. 297-302.
12. Matsuyama, Y., Kataoka, H., Katsumata, N., Shimoda, K., 2004. ICA photographic encoding gear: image bases towards IPEG. Proceedings of the International Joint Conference on Neural Networks, vol. 3, pp. 2129-2134.
13. L.G. Shapiro, and G.C. Stockman Computer Vision 2001 Pearson Education NJ
14. J.Z. Wang, C. Wiederhold, O. Firschein, and S.-X. Wei Content-bases image indexing and searching using Dauechies wavelets International Journal of Digital Libraries 2 1998 311 328
15. H.H. Yang, and S. Amari Adaptive online learning algorithm for blind separation: maximum entropy and minimum mutual information Neural Computation 9 1997 1457 1482