Details of Research Outputs

TitleInnovative Contactless Palmprint Recognition System Based on Dual-Camera Alignment
Author (Name in English or Pinyin)
Liang, Xu1; Li, Zhaoqun2; Fan, Dandan2; Zhang, Bob3; Lu, Guangming4; Zhang, David5
Date Issued2022
Source PublicationIEEE Transactions on Systems, Man, and Cybernetics: Systems
ISSN21682216
EISSN2168-2232
Volume52Issue:10Pages:6464-6476
AbstractRecently, contactless bimodal palmprint recognition technology has attracted increased attention due to the COVID-19 pandemic. Many dual-camera-based sensors have been proposed to capture palm vein and palmprint images synchronously. However, translations between captured palmprint and palm vein images differ depending on the distance between the hand and the sensors. To address this issue, we designed a low-cost method to align the bimodal palm regions for current dual-camera systems. In this study, we first implemented a contactless palm image acquisition device with a dual-camera module and a single-point time of flight (TOF) ranging sensor. Using this device, we collected a dataset named DCPD under different distances and light source intensities from 271 different palms. Then, a bimodal palm image alignment method is proposed based on the imaging and ranging models. After the system model is calibrated, the translation between the visible light and infrared light palm regions can be estimated quickly based on the palm distance. Finally, we designed a convolutional neural network (CNN) to effectively extract the fine- and coarse-grained palm features. Compared to widely used existing methods, the proposed networks achieved the lowest equal error rate (EER) on the Tongji, IITD, and DCPD datasets, and the average time cost of the system to perform one-time identification is approximately 0.15 s. The experimental results indicate that the proposed methods achieved high efficiency and comparable accuracy. In addition, the system's EER and rank-1 on the DCPD dataset were 0.304% and 98.66%, respectively.
KeywordPalmprint recognition Cameras Convolutional neural networks Distance measurement Imaging Image sensors Feature extraction Bimodal palm alignment contactless biometrics convolutional neural network (CNN) palmprint sensor ranging sensor calibration
DOI10.1109/TSMC.2022.3146777
Indexed BySCIE
language英语
Funding ProjectGuangdong Basic and Applied Basic Research Foundation [2019Bl515120055]; Natural Science Foundation of China [62172347, 62176077]; Shenzhen Key Technical Project [2020N046]; Shenzhen Fundamental Research Fund [JCYJ20210324132210025, JCYJ20170412170438636]; Shenzhen Institute of Artificial Intelligence and Robotics for Society [AC01202005018]; Shenzhen Research Institute of Big Data; Medical Biometrics Perception and Analysis Engineering Laboratory, Shenzhen, China
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000754276000001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Original Document TypeArticle
Firstlevel Discipline信息科学与系统科学
Education discipline科技类
Published range国外学术期刊
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Data SourceWOS
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttps://irepository.cuhk.edu.cn/handle/3EPUXD0A/3224
CollectionSchool of Data Science
Shenzhen Institute of Artificial Intelligence and Robotics for Society
Affiliation
1.School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
2.School of Data Science, The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China, and also with the Center for Computer Vision, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518172, China.
3.Department of Computer and Information Science, University of Macau, Macau, China.
4.School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China (e-mail: luguangm@hit.edu.cn).
5.School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China, also with the Center for Computer Vision, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518172, China, and also with the School of Data Science, Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China (e-mail: davidzhang@cuhk.edu.cn)
Recommended Citation
GB/T 7714
Liang, Xu,Li, Zhaoqun,Fan, Dandanet al. Innovative Contactless Palmprint Recognition System Based on Dual-Camera Alignment[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems,2022,52(10):6464-6476.
APA Liang, Xu, Li, Zhaoqun, Fan, Dandan, Zhang, Bob, Lu, Guangming, & Zhang, David. (2022). Innovative Contactless Palmprint Recognition System Based on Dual-Camera Alignment. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(10), 6464-6476.
MLA Liang, Xu,et al."Innovative Contactless Palmprint Recognition System Based on Dual-Camera Alignment".IEEE Transactions on Systems, Man, and Cybernetics: Systems 52.10(2022):6464-6476.
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