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Analysis of performance of palmprint matching with enforced sparsity

Nibouche, O, Jiang, J and Trundle, P (2012) Analysis of performance of palmprint matching with enforced sparsity Digital Signal Processing: A Review Journal, 22 (2). pp. 348-355.

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In this paper, a new and simple palmprint recognition solution based on sparse representation is suggested. It is shown that when the aim is to recover a palmprint from a limited number of observations as a linear combination of measurements of the same palmprint class, the ensuing representation in intrinsically very sparse. It can be efficiently computed by solving an l1 norm convex minimisation problem. When combined with well known subspace feature selection techniques such as PCA and LDA as well as with downsampled images, our tests, which have been carried out on 250 classes of the widely used PolyU database, have yielded an EER as low as 0.11% depending on the palmprints selected during the enrolment phase. Coupled with an execution time as short as 8.4 ms, the obtained results outperform similar work in the literature including EigenPalms, FisherPalms and Gabor based palmprintmatching algorithms, which shows the effectiveness of the new solution.

Item Type: Article
Divisions : Surrey research (other units)
Authors :
Nibouche, O
Trundle, P
Date : 2012
DOI : 10.1016/j.dsp.2011.10.011
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:25
Last Modified : 24 Jan 2020 22:13

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