Indexing and Searching of Image Data in Multimedia Databases Using Axial Projection
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Indexing and Searching of Image Data in Multimedia Databases Using Axial Projection

Authors: Khalid A. Kaabneh

Abstract:

This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.

Keywords: Axial Projection, images, indexing, multimedia database, searching.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060317

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[1] Candocia, F. M., "On the Featureless Registration of Differently Exposed Images," Proceedings of the 2003 International Conference on Imaging Science, Systems and Technology (CISST '03), Vol. I, pp. 163- 169, June 23-26, Las Vegas, Nevada, 2003.
[2] L.G. Brown, "A Survey of Image Registration Techniques," ACM Computing Surveys, Vol. 24, No. 4, pp. 325-376, Dec. 1992.
[3] J.B.A. Maintz and M.A. Viergever, "A Survey of Medical Image Registration," Medical Image Analysis, Vol. 2, No.1, pp. 1-37, 1998.
[4] P.E. Debevec and J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs," Proc. Of SIGGRAPH, pp. 369-378, 1997.
[5] T. Mitsunaga and S. Nayar, "Radiometric Self Calibration," Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 374- 380, 1999.
[6] J. A. Fessler. Improved PET Quantification Using Penalized Weighted Least-Squares Image Reconstruction. IEEE Transaction on Medical Imaging, 1992.
[7] Diaz, A. M., Barros, A. F. and Candocia, F. M., "Image Registration in Range Using a Constrained Piecewise Linear Model: Analysis and New Results," Proceedings of the 2003 International Conference on Imaging Science, Systems and Technology (CISST '03), Vol. I, pp. 152-158, June 23-26, Las Vegas, Nevada, 2003.
[8] A. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, Englewood Cliffs, NJ, 1989.