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Super-Resolution Based ROI Enhancement Approaches for Palmprint Recognition

Erişim

info:eu-repo/semantics/openAccess

Tarih

21 Septemb

Yazar

Macan, Huseyin Furkan
Bingol, Ozkan
Turk, Salih
Ekinci, Murat

Erişim

info:eu-repo/semantics/openAccess

Üst veri

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Künye

Scopus EXPORT DATE: 06 March 2025 @CONFERENCE{MacAn2024, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207966182&doi=10.1109%2fIDAP64064.2024.10710808&partnerID=40&md5=c54ddebd755f9e5fb172be180e825aaf}, affiliations = {Gumushane University, Department of Management Information Systems, Gümüşhane, Turkey; Gumushane University, Department of Software Engineering, Gümüşhane, Turkey; Karadeniz Technical University, Department of Computer Engineering, Trabzon, Turkey}, correspondence_address = {H.F. Macan; Gumushane University, Department of Management Information Systems, Gümüşhane, Turkey; email: huseyinfurkanmacan@hotmail.com}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, isbn = {979-833153149-2}, language = {Turkish}, abbrev_source_title = {Int. Artif. Intell. Data Process. Symp., IDAP} }

Özet

The sizes of regions of interest (ROI) obtained from images captured by cameras in palmprint recognition may vary depending on the camera specifications and the position of the hand. The regions of interest that recognition systems can use are typically rescaled through interpolation techniques and then defined as inputs to the system. In such cases, there may be some loss of biometric data. This study aims to enhance the quality of the palmprint ROI images, which are critical for palmprint recognition systems. To achieve this, various super-resolution techniques were employed to reconstruct low-resolution ROI images to the target sizes while preserving the distinctiveness of their biometric features. This approach is designed to optimize recognition accuracy and improve data reliability in palmprint recognition processes. © 2024 IEEE.

Bağlantı

https://www.scopus.com/record/display.uri?eid=2-s2.0-85207966182&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=40fd9bda90835901e708def55a088591
https://hdl.handle.net/20.500.12440/6427

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