An Efficient De-noising Technique for Fingerprint Image Using Wavelet Transformation
Fingerprint acts as a vital role for user authentication as it is unique and not duplicated. For this reason fingerprint images are taken for different computer security purposes. Unfortunately reference fingerprints may get corrupted with noise during acquisition, transmission, or retrieval from storage media. Many image-processing algorithms such as pattern recognition need a clean fingerprint image to work effectively which in turn needs effective ways of de-noising such images. In this paper, we propose an adaptive method of image de-noising in the wavelet sub-band domain assuming the images to be contaminated with noise based on threshold estimation for each sub-band. Under this framework, the proposed technique estimates the threshold level by apply sub-band of each decomposition level. This paper entails the development of a new MATLAB function based on our algorithm. The experimental evaluation of our proposition reveals that our method removes noise more effectively than the in-built function provided by MATLAB.
KeywordsWavelet Thresholding Gaussian Salt & Pepper noise Fingerprint Image De-noise Discrete Wavelet Transform
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