Application of l1 norm minimization technique to image retrieval

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Sastry, Saurabah Jain and Ashish Mishra: Application of l1 norm minimization technique to image retrieval. WASET, Vol.56, No.145, pp.801-804, 2009



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.

Extended Abstract


author = {Sastry, Saurabah Jain and Ashish Mishra},
title = {Application of l1 norm minimization technique to image retrieval},
journal = {WASET, World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering},
volume = {56},
number = {145},
pages = {801-804},
year = {2009},

Used References

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