Title: Palmprint recognition through the fractal dimension estimation for texture analysis

Authors: Raouia Mokni; Monji Kherallah

Addresses: Faculty of Economics and Management of Sfax, University of Sfax, Road Aeroport Km 4, 3018 Sfax, Tunisia ' Faculty of Sciences of Sfax, University of Sfax, Road Soukra Km 3, 3038 Sfax, Tunisia

Abstract: Palmprint is a human physiological feature which can distinguish and identify one person from another. In the palmprint recognition biometric systems, the feature extraction is considered as the most important step. In this paper, we use the fractal approach which is both a very advanced and sophisticated method in order to extract the palmprint texture information features. This approach has been widely used in recent years being considered as an active research area in the image processing field. Therefore, we have implemented a new technique to extract the palmprint texture features: the texture analysis basing on the fractal dimension estimated via the box-counting method or TAFD-BC. Experimental results on the PolyU 2D Palmprint database prove that our proposed approach produces promising and favourable results compared to other well-known state-of-the-art techniques.

Keywords: biometrics; palmprints; texture analysis; fractal dimension; box counting; identification; palmprint recognition; feature extraction; texture features.

DOI: 10.1504/IJBM.2016.082599

International Journal of Biometrics, 2016 Vol.8 No.3/4, pp.254 - 274

Available online: 27 Feb 2017 *

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