Application of l1-Norm Minimization Technique to Image Retrieval
Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1080918Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3044
 P. Brodatz, Textures: A photographic album for artists and designers, Dover Publication, New York, 1996.
 A. M. Bruckstein, D. L. Donoho and M. Elad, From sparse solutions of systems of equations to sparse modeling of signals and images, SIAM Review, vol. 51, No. 1, pp: 34-81, 2009.
 E. Candes and J. Romberg, l1 magic: Recovery of sparse signals via convex programming, http://www.acm.caltech.edu/l1magic/, 2005.
 E. Candes and J. Romberg and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Comm. Pure and Applied Maths, 59, 1207-1223, 2006.
 S. Chen and D. Donoho and M. Saunders, Atomic decomposition by basis pursuit, SIAM Review, 43(1), 129-159, 2001.
 D. Donoho, For most large underdetermined systems of linear equations the minimal l1-norm near solution approximates the sparsest solution, Comm. Pure and Applied Maths, 59(10), 907-34, 2006.
 B. S. Manjunath and Y. S. Ma, Texture features for browsing and retrieval of image data, IEEE T. on Pattern Analysis and Machine Intelligence, 18(8):837-842, 1996.
 C. S. Sastry and M. Ravindranath and A. K. Pujari B. L. Deekshatulu, A modified Gabor method for content based image retrieval, Pattern Recognition Letters, 28, 293-300, 2007.