This article presents an extended author's version based on our previous work, where we introduced the Multiple Overlapping Tiles (MOT) method for palm vein image enhancement. To better reflect the specific operations involved, we rename MOT to ILACS-LGOT (Intensity-Limited Adaptive Contrast Stretching with Layered Gaussian-weighted Overlapping Tiles). This revised terminology more accurately represents the method's approach to contrast enhancement and blocky effect mitigation. Additionally, this article provides a more detailed analysis, including expanded evaluations, graphical representations, and sample-based comparisons, demonstrating the effectiveness of ILACS-LGOT over existing methods.
@article{arxiv.2502.19456,
title = {ILACS-LGOT: A Multi-Layer Contrast Enhancement Approach for Palm-Vein Images},
author = {Kaveen Perera and Fouad Khelifi and Ammar Belatreche},
journal= {arXiv preprint arXiv:2502.19456},
year = {2025}
}
Comments
Our previous work, A Keypoint Filtering Method for SIFT based Palm-Vein Recognition, presented at the 2022 CoDIT and published in IEEE Xplore (DOI: 10.1109/CoDIT55151.2022.9804034). The code for the ILACS-LGOT method is available at: https://github.com/kaveenperera/ILACS-Enhancement under Mozilla Public License Version 2.0