Visibility Restoration via Smoothing Speed for Vein Recognition

Kim, Wonjun

doi:10.1587/transinf.2018edl8110

Cited by 1 publication

(1 citation statement)

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“…The intensity difference between the original image and a smoothed version which is referred to as smoothing speed has been used to differentiate vein patterns from the background. A common issue observed with [12] [13] [14] is that these image smoothing techniques discard vital subspace information which can be used to detect robust features. Trabelsi et al [15] calculated the global mean grey and variance values, then used a convolutional kernel which take the global mean and variance along with an enhancement constant into account to calculate the local response.…”

Section: Related Workmentioning

confidence: 99%

A Novel Image Enhancement Method for Palm Vein Images

Perera

Khelifi

Belatreche

2022

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)

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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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Section: Related Workmentioning

confidence: 99%