Open Access   Article Go Back

Effectiveness of Symlets in De-noising Fingerprint Images

T.N. Tilak1 , S. Krishnakumar2

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-12 , Page no. 29-34, Dec-2015

Online published on Dec 31, 2015

Copyright © T.N. Tilak , S. Krishnakumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: T.N. Tilak , S. Krishnakumar , “Effectiveness of Symlets in De-noising Fingerprint Images,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.12, pp.29-34, 2015.

MLA Style Citation: T.N. Tilak , S. Krishnakumar "Effectiveness of Symlets in De-noising Fingerprint Images." International Journal of Computer Sciences and Engineering 3.12 (2015): 29-34.

APA Style Citation: T.N. Tilak , S. Krishnakumar , (2015). Effectiveness of Symlets in De-noising Fingerprint Images. International Journal of Computer Sciences and Engineering, 3(12), 29-34.

BibTex Style Citation:
@article{Tilak_2015,
author = {T.N. Tilak , S. Krishnakumar },
title = {Effectiveness of Symlets in De-noising Fingerprint Images},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2015},
volume = {3},
Issue = {12},
month = {12},
year = {2015},
issn = {2347-2693},
pages = {29-34},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=736},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=736
TI - Effectiveness of Symlets in De-noising Fingerprint Images
T2 - International Journal of Computer Sciences and Engineering
AU - T.N. Tilak , S. Krishnakumar
PY - 2015
DA - 2015/12/31
PB - IJCSE, Indore, INDIA
SP - 29-34
IS - 12
VL - 3
SN - 2347-2693
ER -

VIEWS PDF XML
2961 2501 downloads 2378 downloads
  
  
           

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.

Key-Words / Index Term

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

References

[1] Minakshi Kumar, “Satellite Remote Sensing and GIS Applications in Agricultural Meteorology”, Proceedings of a Training Workshop on Digital Image Processing held at Dehra Dun, India, Page No.(81-102), . July 7-11, 2003.
[2] P P Vaidyanathan and Igor Djokovic, “An Introduction to Wavelet Transforms”, California Institute of Technology, Page No. (1-116), .1994.
[3] P L Patil and V B Raskar,”MRI Images Techniques”, Int. Journal of Advancd Research in Computer and Communication Engineering, Vol-04, Issue-02, Page No.(304-308), Feb 2015, ISSN 22278-1021.
[4] J Kaur and R Kaur, “Biomedical Images denoising using Symlet Wavelet with Wiener filter”, Int. Journal of Engineering Research and Applications, Vol-03, Issue-03, Page No..(548-550), May-Jun 2013, ISSN: 2248-9622.
[5] T Varma, V Chitre and D Patil, “The Haar Wavelet and The Biorthogonal Wavelet Transforms of an Image”, National Conference on Emerging Trends in Engineering & Technology (VNCET), 30 Mar2012, Page No.(288-291), .Int. Journal of Engineering Research and Applications.
[6] I Daubechies, “Ten Lectures on Wavelets”, Regional Conference Series in Applied Mathematics, SIAM, 1992. ISBN 978-0-89871-274-2.
[7] G. Strang and T. Nguyen, “Wavelets and Filter Banks”, Wellesley-Cambridge Press, Second Edition, ISBN-13: 978-0961408879, 1996.
[8] V Singh and R Sharma, “Wavelet Based Method for Denoising of Electroencephalogram”, Int. Journal of Advanced Research in Computer Science and Software Engineering, Vol-05, Issue -04, Page No. (1113-1117), April 2015, ISSN: 2277 128X.
[9] Myung-S Song, ‘Wavelet Image Compression’, Page No.(1-33), Mathematics Subject Classification. Primary 42C40. Contemporary Mathematics, Southern Illinois, University Edwardsville, Edwardsville, USA. 1991
[10] L Passrija, A S Virk and M Kaur, “Performance Evaluation of Image Enhancement Techniques in Spatial and Wavelet Domains”, Int. Journal of Computers & Technology, Volume - 03, No.- 01, Page No. (162-166), Aug 2012, ISSN: 2277- 3061.
[11] P Gravel, G Beaudoin and J A D Guise, “A Method for Modeling Noise in Medical Images”, IEEE TRANSACTIONS ON MEDICAL IMAGING, Vol--23, No.- 10, Page No.(1221-1232), Oct 2004.
[12] Sumit Kushwaha and Dr. Rabindra Kumar Singh, “ Study of Various Image Noises and Their Behavior”, Int. Journal of Computer Sciences and Engineering,Vol-03, Issue-03, Page No.(13-17), Mar 2015, ISSN: 2347-2693.V
[13] T N Tilak and S Krishnakumar, “De-noising with Different Bi-orthogonal Spline Wavelets using DWT ”, Int. Journal of Engineering Research & Technology, Vol-04, Issue- 04, Page No. (238-242), April 2015, ISSN:2278-0181. DOI: 10.17577/IJERTV4IS040422., Issue-
[14] P Rajput and S K S Tomar, “Development of Novel Denoising Technique using Total Variation and Symlet Wavelet Filter”, Int Journal of Engineering Trends and Technology, Vol - 22, No.- 03, Page No.(109-114), April 2015, ISSN: 2231-5381.
[15] G Chang, B Yu, and M Vetterli, “Adaptive Wavelet Thresholding for Image Denoising and Compression”, IEEE TRANSACTIONS ON MEDICAL IMAGING, Vol.-09, No.-09, Page No. ( 1532- 1546), Sept 2000.
[16] H Om and M Biswas, “An Improved Image Denoising Method Based on Wavelet Thresholding”, Journal of Signal and Information Processing, 3, Page No. (109-116), Feb 2012, ISSN: 2159-4481
[17] F Luisier, T Blu, and M Unser, “A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding”, IEEE TRANSACTIONS ON IMAGE PROCESSING, Vol-16, No.-03, Page No.(593-606), Mar 2007.