A novel image enhancement method for palm vein images

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)
149 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Control, Decisions and Information Technologies (CODIT 2022)
Subtitle of host publication(CODIT 2022)
Place of PublicationPiscataway, NJ
PublisherIEEE
Number of pages6
ISBN (Electronic)9781665496063
ISBN (Print)9781665496070
DOIs
Publication statusPublished - 17 May 2022
Event8th International Conference on Control, Decision and Information Technologies: CoDIT'22 - Istanbul, Turkey
Duration: 17 May 202220 May 2022
https://codit2022.com/

Conference

Conference8th International Conference on Control, Decision and Information Technologies
Country/TerritoryTurkey
CityIstanbul
Period17/05/2220/05/22
Internet address

Fingerprint

Dive into the research topics of 'A novel image enhancement method for palm vein images'. Together they form a unique fingerprint.

Cite this