Effectiveness of Symlets in De-noising Fingerprint Images

Authors

  • TN Tilak School of Technology & Applied Sciences,Mahatma Gandhi University Regional Centre, Edappally, Kochi-682 024, India
  • S Krishnakumar School of Technology & Applied Sciences,Mahatma Gandhi University Regional Centre, Edappally, Kochi-682 024, India

Keywords:

Symlets, Vanishing moments, Orthhogonal wavelets, Discrete wavelet transform, AWGN, Thresholding

Abstract

This paper examines the effectiveness of symlets in de- noising fingerprint images. The 'fingerprint' test image is corrupted with Additive White Gaussian Noise and the noisy image is de-noised using Discrete Wavelet Transform employing symlet wavelets of different orders. The effectiveness of de-noising with each member of the selected set of members of the symlet wavelet family is examined with the standard performance measures namely the MSE and PSNR, along with the apparent visual quality of the de-noised images. The study is repeated with a set of random values for the noise variance.

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Published

2025-11-11

How to Cite

[1]
T. Tilak and S. Krishnakumar, “Effectiveness of Symlets in De-noising Fingerprint Images”, Int. J. Comp. Sci. Eng., vol. 3, no. 12, pp. 29–34, Nov. 2025.

Issue

Vol. 3 No. 12 (2015): IJCSE December Edition

Section

Research Article

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