Contactless Palmprint Recognition using Deep Learning Technology


  • admin



Contactless Palmprint, Image, Biometrics Techniques, Deep Learning, Recognition.


The interest of researchers in the subject of biometrics has increased, which has opened new horizons in people identification systems, and one of these measurements is the contactless palm print. Identification of people through a contactless palm print is very important in the process of identifying terrorists and criminals whose faces are often covered. Therefore, a contactless palm print recognition system has been proposed through two pre-processing methods using a neural network. A Contrast Limited Adaptive Histogram Equalization (CLAHE) filter was used in the first processing of the data stage as well as the normalization method. The system was applied to several databases, including the standard Indian Institute of Technology Delhi (IITD) ones, and those collected from the Computer Department, College of Science, University of Diyala, After the process of data division, training and testing, the proposed system reached satisfactory results compared to previous work, and the accuracy was 99.95.


K. Jain, J. K. Feng Anil Jain, J. Feng, and I. Trans PAMI, “Latent Palmprint Matching Under Review in,” 1–35, 2008.

W. Wu, S. J. Elliott, S. Lin, S. Sun, and Y. Tang, “Review of palm vein recognition,” IET Biometrics, 9)1(, 1–10, 2020

S. C. Soh, M. Z. Ibrahim, and M. B. Yakno, “A review: Personal identification based on palm vein infrared pattern,” J. Telecommun. Electron. Comput. Eng., vol. 10, no. 1–4, 175–180, 2018.

Mokni, Raouia; Kherallah, Monji (2016). Novel palmprint biometric system combining several fractal methods for texture information extraction. , 002267–002272

S. Kaushik and R. Singh, "A new hybrid approach for palmprint recognition in PCA based palmprint recognition system," 2016 5th Int. Conf. Reliab. Infocom Technol. Optim. ICRITO 2016 Trends Futur. Dir., no. September, 239–244, 2016

Bilal Attallah, Amina Serir, Youssef Chahir (2017). Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction, J. Electron. Imaging 26(6), 063006

A. Younesi and M. C. Amirani, “Gabor Filter and Texture based Features for Palmprint Recognition,” Procedia Comput. Sci., 108, 2488–2495, 2017

P. Dataset, "SS symmetry Palmprint and Palmvein Recognition Based on, 1–15, 2018

H. Shao, D. Zhong, and X. Du, "CROSS-DOMAIN PALMPRINT RECOGNITION BASED ON TRANSFER CONVOLUTIONAL AUTOENCODER School of Electronic and Information Engineering, Xi ' an Jiaotong University, 28 West Xianning Road, Xi ' an Shaanxi 710049, P . R . China," 2019 IEEE Int. Conf. Image Process., 1153–1157, 2019.

A. Verma, “Personal Palm Print Identification Using KNN Classifier, 7)4(, 2019.

M. Sowmiya Manoj and S. Arulselvi, "Palmprint identification and classification using KNN algorithm," Mater. Today Proc., no. XXXX, pp. 10–12, 2021

A. Mishra, “Multimodal Biometrics it is: Need for Future Systems,” Int. J. Comput. Appl., 3)4(, 28–33, 2010

L. Fei, G. Lu, W. Jia, S. Teng, and D. Zhang, “Feature extraction methods for palmprint recognition: A survey and evaluation,” IEEE Trans. Syst. Man, Cybern. Syst., 49)2(, 346–363, 2019

Q. Zheng, A. Kumar, and G. Pan, “Suspecting Less and Doing Better: New Insights on Palmprint Identification for Faster and More Accurate Matching,” IEEE Trans. Inf. Forensics Secur., 11)3(, 633–641, 2016

J. Funada et al., "Feature extraction method for palmprint considering elimination of creases," no. September 1998, 1849–1854, 2002

L. Wu, Y. Xu, Z. Cui, Y. Zuo, S. Zhao, and L. Fei, “Triple-type feature extraction for palmprint recognition,” Sensors, 21)14(,1–15, 2021

L. Fei, B. Zhang, W. Jia, J. Wen, and D. Zhang, “Feature Extraction for 3D Palmprint Recognition : A Survey,” IEEE Trans. Instrum. Meas., vol. PP, no. c, p. 1, 2020

F. Liu, L. Zhou, Z. M. Lu, and T. Nie, “Palmprint feature extraction based on curvelet transform,” J. Inf. Hiding Multimed. Signal Process., 6)1(,131–139, 2015.

M. Izadpanahkakhk, S. M. Razavi, M. Taghipour-Gorjikolaie, S. H. Zahiri, and A. Uncini, “Deep region of interest and feature extraction models for palmprint verification using convolutional neural networks transfer learning,” Appl. Sci., 8) 7(,1–20, 2018

P. Manegopale, “A Survey on Palmprint Recognition,” 3)2(,9085–9094, 2014.

J. P. Patil, C. Nayak, M. T. C. S. Engineering, and B. M. C. Technology, “A Survey of Multispectral Palmprint Identification Techniques,” 1053)3(,1051–1053, 2014.

S. Lin, T. Xu, and X. Yin, “Region of interest extraction for palmprint and palm vein recognition,” Proc. - 2016 9th Int. Congr. Image Signal Process. Biomed. Eng. Informatics, CISP-BMEI 2016, no. October 2016, 538–542, 2017




How to Cite

admin. (2024). Contactless Palmprint Recognition using Deep Learning Technology. Academic Science Journal, 2(1), 361–370.