Recognition of Finger mark using CNN

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Published Jan 25, 2023

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M. Naga Triveni
Assistant Professor, Department of Computer Science Engineering AIML, St. Martins Engineering College, Secunderabad, Telangana, India.

Abstract

In present-days, the technological development in the field of data collection, processing, storing along with the field of research in pattern recognition, machine learning and deep learning serves a biometric person recognition processing fingerprint. In this work, the proposed model is a classification system to recognize and match images of fingerprints. ACNN architecture is used to develop a model for detection. The present study uses approach to ensure the performance of the system. Finger print recognition system used for identifies the entity who involved in the database helps to automate fingerprint identification process. Preprocessing was performed with fingerprint thinning and minutiae extraction with method. Feature extraction will be done by the CNN classifier.

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Issue
Vol 10 No 1 (2023): Volume 10 Issue 1
Section
Articles

References

[1]. Neeraj Bharagava, Anchal Kumawat, Ritu Bharagava (2015). “Fingerprint Matching of Normalized Image based on Euclidean Distance”. International Journal of computer Application.Volume120-No 24.
[2]. R.Donidalabati, A.Genovese, V.Piuri and F.Scotti,” Touchless Finger print Biometrics: A survey on 2D and 3DTechnologies”,injournalofinternettechnology, 2014.
[3]. A. Ross and A. Jain, “Biometric sensor interoperability: A case study in fingerprints.” Proc. Bio AW,LNCS 3086, Springer, 2004, pp. 134–145. 17. Arun Ross and Rohan Nadgir, “A Thin-Plate Spline Calibration Model.
[4]. KarenSimonyan Andrew Zisserman,” Two-Stream Convolutional Networks for Action Recognition in Videos”, Neural Information Processing Systems, 2014,Vol1,pp.568-5.
[5]. V. Piuri and F. Scotti, “Fingerprint biometrics via low-cost sensors and webcams,” in Proc. 2nd IEEE Inte. Conf. onBiometrics: Theory, Applications and Systems, October 2008,pp. 1–6.
[6]. F. Han, J. Hu, M. Alkhathami, and K. X “Compatibility of photographed images with touch-basedfingerprintverificationsoftware,” inProc.IEEE Conf.onIndustrial ElectronicsandApplications,June2011, pp. 1034 – 1039.
[7]. H. Choi, K. Choi, and J. Kim, “Mosaicing touchless and mirrorreflected fingerprint images,” IEEETrans.Inf.ForensicsSecurity,vol. 5, no. 1,pp. 52– 61,March 2010.