Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process

Sarra Hajri; Fathi Kallel; Ahmed Ben Hamida; Amine Nait-Ali

doi:10.1117/1.JEI.27.3.033035

14 June 2018 Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process

Sarra Hajri, Fathi Kallel, Ahmed Ben Hamida, Amine Nait-Ali

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 3, 033035 (June 2018). https://doi.org/10.1117/1.JEI.27.3.033035

Abstract

Finger-knuckle-print (FKP) is considered as one of the emerging hand biometric traits due to its potentiality toward the identification of individuals. However, extracting features out of poor contrast FKP images is the most challenging problem faced in this area. We propose a method for personal recognition using FKP images based on a preprocessing step to improve the contrast of input FKP image and a processing step for features extraction. In the first part, we compared the performances of different histogram equalization-based contrast enhancement algorithms. The enhanced image with better performance is considered in a second step for feature extraction and personal identification. We experimentally compared the proposed approach to other existing approaches in literature using PolyU FKP database framework, and results show that our technique performed favorably.

Citation Download Citation

Sarra Hajri, Fathi Kallel, Ahmed Ben Hamida, and Amine Nait-Ali "Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process," Journal of Electronic Imaging 27(3), 033035 (14 June 2018). https://doi.org/10.1117/1.JEI.27.3.033035

Received: 24 January 2018; Accepted: 22 May 2018; Published: 14 June 2018

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