ICTACT Journal on Image and Video Processing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Palm Vein Classification from Large Datasets Using Deep Convolutional Fusion Learning


Affiliations
1 Department of Information Technology, Karpagam Institute of Technology, India
2 Department of Computer Science and Engineering, SNS College of Engineering, India
3 Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, India
     

   Subscribe/Renew Journal


Biometric techniques are currently among the most widely used methods all over the world for determining a person identity. This trend is expected to continue in the near future. In this study, we focused on palm vein is used as a strategy to improve biometric authentication systems by combining a method that is based on texture with a method that is based on a convolutional neural network (CNN). The simulation is used to test the performance of the model on several different datasets. In simulations, the suggested method routinely achieves better results than the current best practice on each and every dataset.

Keywords

Palm Vein, Classification, Convolutional Neural Network.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Y.Y. Fanjiang, “Palm Vein Recognition based on Convolutional Neural Network”, Informatica, Vol. 32, No. 4, pp. 687-708, 2021.

  • S. Li and B. Zhang, “Joint Discriminative Sparse Coding for Robust Hand-Based Multimodal Recognition”, IEEE Transactions on Information Forensics and Security, Vol. 16, pp. 3186-3198, 2021.

  • R. Hernandez-Garcia and N. Guil, “Large-Scale Palm Vein Recognition on Synthetic Datasets”, Proceedings of International Conference of the Chilean Computer Science Society, p. 1-8, 2021.

  • R.A. Mustafa, “Palm Print Recognition based on Harmony Search Algorithm”, International Journal of Electrical and Computer Engineering, Vol. 11, No. 5, pp. 1-12, 2021.

  • H.N. Bendini and D.D.M. Valeriano, “Exploring a Deep Convolutional Neural Network and Geobia for Automatic Recognition of Brazilian Palm Swamps (Veredas) using Sentinel-2 Optical Data”, Proceedings of IEEE International Conference on Geoscience and Remote Sensing, pp. 5401-5404, 2021.

  • A.S. Al Jaberi and A.M. Al-juboori, “Palm Vein Recognition based on Convolution Neural Network”, Journal of Al-Qadisiyah for Computer Science and Mathematics, Vol. 13, No. 3, pp. 1-6, 2021.

  • A.S.M. Htet and H.J. Lee, “TripletGAN VeinNet: Palm Vein Recognition Based on Generative Adversarial Network and Triplet Loss”, Proceedings of International Conference on Computer Engineering and Artificial Intelligence, pp. 454-458, 2021.

  • S. Athisayamani, A. Robert Singh and A. Sivanesh Kumar, “Recurrent Neural Network-Based Character Recognition System for Tamil Palm Leaf Manuscript using Stroke Zoning”, Proceedings of International Conference on Inventive Communication and Computational Technologies, pp. 165-176, 2021.

  • X. Liang and D. Zhang, “CompNet: Competitive Neural Network for Palmprint Recognition Using Learnable Gabor Kernels”, IEEE Signal Processing Letters, Vol. 28, pp. 1739-1743, 2021.

  • K. Zhang and Tao, “Class Constraint-based Discriminative Features Learning Algorithm for Palm Print and Palm Vein Fusion Recognition”, Proceedings of International Conference on Signal and Image Processing, pp. 275-280, 2022.

  • G. Ananthi and S. Arivazhagan, “Human Palm Vein Authentication using Curvelet Multiresolution Features and Score Level Fusion”, The Visual Computer, Vol. 38, No. 6, pp. 1901-1914, 2022.


Abstract Views: 161

PDF Views: 1




  • Palm Vein Classification from Large Datasets Using Deep Convolutional Fusion Learning

Abstract Views: 161  |  PDF Views: 1

Authors

B. Chellapraba
Department of Information Technology, Karpagam Institute of Technology, India
K. Periyakaruppan
Department of Computer Science and Engineering, SNS College of Engineering, India
D. Manohari
Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, India
M.S. Kavitha
Department of Computer Science and Engineering, SNS College of Engineering, India

Abstract


Biometric techniques are currently among the most widely used methods all over the world for determining a person identity. This trend is expected to continue in the near future. In this study, we focused on palm vein is used as a strategy to improve biometric authentication systems by combining a method that is based on texture with a method that is based on a convolutional neural network (CNN). The simulation is used to test the performance of the model on several different datasets. In simulations, the suggested method routinely achieves better results than the current best practice on each and every dataset.

Keywords


Palm Vein, Classification, Convolutional Neural Network.

References