A novel image enhancement method for palm vein images

Perera, Kaveen, Khelifi, Fouad and Belatreche, Ammar (2022) A novel image enhancement method for palm vein images. In: Proceedings of the IEEE International Conference on Control, Decisions and Information Technologies (CODIT 2022). IEEE, Piscataway, NJ, pp. 1-6. ISBN 9781665496070; 9781665496063

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Abstract

Palm vein images usually suffer from low contrast due to skin surface scattering the radiance of NIR light and image sensor limitations, hence require employing various techniques to enhance the contrast of the image prior to feature extraction. This paper presents a novel image enhancement method referred to as Multiple Overlapping Tiles (MOT) which adaptively stretches the local contrast of palm vein images using multiple layers of overlapping image tiles. The experiments conducted on the CASIA palm vein image dataset demonstrate that the MOT method retains the finer subspace details of vein images which allows excellent feature detection and matching with SIFT and RootSIFT features. Results on existing palm vein recognition systems demonstrate that the proposed MOT method delivers lower EER values outperforming other existing palm vein image enhancement methods.

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