Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30077
Local Image Descriptor using VQ-SIFT for Image Retrieval

Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi


In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventional algorithm while the computational cost is significantly reduced.

Keywords: SIFT feature, Vector quantization histogram, Localdescriptor, Image retrieval.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2016


[1] C. Harris and M. Stephens, "A combined corner and edge detector," In Alvey Vision Conference, 1988, pp. 147-151.
[2] D. G. Lowe, "Object recognition from local scale- invariant features," In Proceedings of International Conference on Computer Vision, 1999, pp.1150-1157.
[3] W. T. Freeman and E. H. Adelson, "The design and use of steerable filters," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.13, no.9, 1991, pp. 891-906.
[4] J. Koenderink and A. van Doorn, "Representation of local geometry in the visual system," In Biological Cybernetics, vol.55, 1987, pp. 367-375.
[5] F. Schaffalitzky and A. Zisserman, "Multi-view matching for unordered image sets," In Proceedings of European Conference on Computer Vision, vol.1, 2002, pp. 414-431.
[6] L. Van Gool, T. Moons, and D. Ungureanu, "Affine/photometric invariants for planar intensity patterns," In Proceedings of European Conference on Computer Vision, 1996.
[7] D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, vol.60, no.2, 2004, pp. 91-110.
[8] R. Fergus, P. Perona, and A. Zisserman, "Object class recognition by unsupervised scale-invariant learning," In Proceedings of Computer Vision and Pattern Recognition, Jun. 2003.
[9] K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," In Proceedings of Computer Vision and Pattern Recognition, Jun. 2003.
[10] K. Kotani, Q. Chen, and T. Ohmi, "Face recognition using vector quantization histogram method," In Proceedings of 2002 International Conference on Image Processing, vol. II of III:II-105-II-108, 2002.
[11] A.Gersho and R.M.Gray, Vector Quantization and Signal Compression, Kluwer Academic, 1992.
[12] W. T. Freeman and M. Roth, "Orientation histograms for hand gesture recognition," In Proceedings of International Workshop on Automatic Face and Gesture Recognition, IEEE Computer Society, Zurich, Switzerland, 1995, pp. 296-301.
[14] AT&T Laboratories Cambridge, The Database of Faces, at
[16] T. Deselaers, D. Keysers, and H. Ney, "Features for image retrieval - a quantitative comparison", 26th DAGM Symposium, vol. 3175 of Lecture Notes in ComputerScience , Germany, pp. 228-236, 2004.
[17] Q. Chen, K. Kotani, F. F. Lee, and T. Ohmi, "Robust VQ-based Local Descriptor for SIFT Feature," Proceeding of the International Conference on Image and Vision Computing (ICIVC 2009), pp. 1329-1333, France, Jun. 2009.
[18] H. Tamura, S. Mori, and T. Yamawaki, "Textural features corresponding to visual perception", IEEE Transaction on Systems, Man, and Cybernetics, vol. 8, no. 6, 460-472, 1978.