Authentication System Based Palmprint Recognition Using Simple Structured Neural Network
Abstract
Biometrics technology is gaining popularity every day. In most countries nowadays, academics are focusing their efforts on biometrics because it has an important function in security. Analyzing a large number of security cases provided researchers with significant motivation to conduct additional research and develop new ideas. Biometrics technology also has multiple uses outside of the security industry, including civil, commercial, and industrial applications. Biometrics measures and analyzes unique physical and behavioral characteristics of people. Palmprints are currently considered the preferred biometric for application in highly sensitive access control environments such as federal buildings, airports, and other critical locations. Palmprint contains a more distinctive feature and does not require a high-resolution palmprint image, unlike other biometric characteristics. This paper involves designing of high accuracy palm recognition system using simple structured neural network called single hidden layer neural network. accuracy score for the proposed state of the art is found 91.3 %.
References
[2] M. K. Shaveta Dargan, "A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities," Expert Systems with Applications, vol. 2020, 143.
[3] N. K. C. E. E. Murat Taskiran, "Face recognition: Past, present and future (a review)," Digital Signal Processing, vol. 2020, 106.
[4] X. Z. S. G. Zhiyi Cheng, "Face re-identification challenge: Are face recognition models good enough?," Pattern Recognition, vol. 2020, 107.
[5] Y. X. J. H. J. Z. B. Z. Yuhao Bai, "Accurate prediction of soluble solid content of apples from multiple geographical regions by combining deep learning with spectral fingerprint features," Postharvest Biology and Technology, vol. 156, 2019.
[6] B. Z. Y. X. W. J. J. W. J. W. Lunke Fei, "Precision direction and compact surface type representation for 3D palmprint identification," Pattern Recognition, vol. 87, 2019.
[7] K. K. M. T. D. R. R. P. S. C. A. K. P. Rama Vasantha Adiraju, "An extensive survey on finger and palm vein recognition system," in Materials Today: Proceedings, 2020.
[8] A. K. R. N. Gaurav Jaswal, "Multiple feature fusion for unconstrained palm print authentication," Computers & Electrical Engineering, vol. 72, 2018.
[9] C. H. L. C. F. K. Han C, "Personal authentication using palm-print features," Pattern Recognit , vol. 36, 2003.
[10] W. K. F. D. Q. W. Xuekui Yan, "Palm vein recognition based on multi-sampling and feature-level fusion," Neurocomputing, vol. 151, 2015.
[11] T. Chai, "Boosting palmprint identification with gender information using DeepNet," Future Generation Computer Systems, vol. 99, 2019.
[12] J. Xiaojun, "Palm vein recognition method based on fusion of local Ga- bor histograms," J. China Univ. Posts Telecommun, vol. 24 , 2017.
[13] S. A. F. Hafiz Imtiaz, "A histogram-based dominant wavelet domain feature selection algorithm for palm-print recognition," Computers and Electrical Engineering, vol. 39, 2013.
[14] T. C. A. B. J. T. Goh Kah Ong Michael, "Touch-less palm print biometrics: Novel design and implementation," Image and Vision Computing, vol. 26, 2008.
[15] M. P. Kamila Ciężar, "2D fourier transform for global analysis and classification of meibomian gland images," The Ocular Surface, vol. 18, 2020.
[16] S. R. Akshi Kumar, "Edge Detection using Guided Image Filtering and Enhanced Ant Colony Optimization," Procedia Computer Science, vol. 173, 2020.
[17] R. F. V. V. M. F. R. C. Sérgio F. Chevtchenko, "A convolutional neural network with feature fusion for real-time hand posture recognition," Applied Soft Computing, vol. 73, 2018.
[18] A. B. K. M. S. B. Safa Ameur, "A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with Leap Motion," Entertainment Computing, vol. 35, 2020.
[19] J. F. M.-T. R. M. V. R. J. A. C. O. A. Y. R. G. M. S. L. C. Gretel Bernal Baró, "A PSO-based algorithm for mining association rules using a guided exploration strategy," Pattern Recognition Letters, vol. 138, 2020.
[20] M. L. F. A. R. A. F. M. J.-M. R. Maxime Metz, "A “big-data” algorithm for KNN-PLS," Chemometrics and Intelligent Laboratory Systems, vol. 203, 2020.
[21] Pune college of engineering palm images database: last access 22/03/ 2021: https://www.coep.org.in/resources/coeppalmprintdatabase
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