Performance Analysis of Fingerprint Denoising Using Stationary Wavelet Transform

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Usha.S 1,* Kuppuswami.S 1

1. Kongu Engineering College, Perundurai-638052, Tamilnadu, India

* Corresponding author.


Received: 11 Jun. 2015 / Revised: 25 Jul. 2015 / Accepted: 7 Sep. 2015 / Published: 8 Oct. 2015

Index Terms

Denoising, Fingerprint, Normal Shrink, Visu Shrink, Quality Metrics, Stationary Wavelet Transform


Finger print is the finest and cheapest recognition system because of its easy extraction of unique features like bifurcation and termination. But the quality of fingerprint data are easily degraded by dryness of skin, wet, wound and other types of noises. Hence, denoising of fingerprint image is vital step for automatic fingerprint recognition system. In the proposed paper the removal of noise from fingerprint images by using stationary wavelet transform and adaptive thresholding method is analysed. The proposed algorithm is developed using MATLAB (R2010b) and tested in the fingerprint images collected from FVC2004 database and R303A optical scanner. The performance of the method is analysed by calculating the quality metrics like Peak Signal to Noise Ratio, Universal Quality Index , Structure Similarity and Multi-Scale Structure Similarity (MS-SSIM). The quality of fingerprint image after noise removal using proposed analysis confirms the suggested method is better than the conventional techniques.

Cite This Paper

Usha.S, Kuppuswami.S,"Performance Analysis of Fingerprint Denoising Using Stationary Wavelet Transform", IJIGSP, vol.7, no.11, pp.48-54, 2015. DOI: 10.5815/ijigsp.2015.11.07


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