Palm print Recognition using 2D Fourier Transformation and Integration Function

Authors

  • Abhilove Kumar  Department of Computer Science and Engineering, Naraina Vidya Peeth Engineering & Management Institute, Kanpur, India
  • Apoorv Mishra  Department of Computer Science and Engineering, Naraina Vidya Peeth Engineering & Management Institute, Kanpur, India

DOI:

https://doi.org//10.32628/CSEIT2173165

Keywords:

Machine Learning, Palm print, Histogram, Minutiae

Abstract

Palm print authentication technique is very powerful technique as compare with other technique and it is also very friendly with the user and environment. Palm is the mainly inner part of the hand which shows different features as compare with other in this it technique it mainly provide the path to authenticate the user or modify the user. In this technique we use phase based matching algorithm and if in this problems will occur then it reduce by using of Fourier Transform technique and Integration system. These techniques extract the features of the palm to modify it and there are so many features for extraction. In this we authenticate the user with applying some of the transformation where when we extract the feature vector then it will not give the accurate result. That's why we using this transformation technique in this which is very useful for the user.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-06-30

Issue

Volume 7, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Abhilove Kumar, Apoorv Mishra, " Palm print Recognition using 2D Fourier Transformation and Integration Function, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.555-560, May-June-2021. Available at doi : https://doi.org/10.32628/CSEIT2173165