A Fast Algorithm for Salt-and-Pepper Noise Removal with Edge Preservation Using Cardinal Spline Interpolation for Intrinsic Finger Print Forensic Images
The accuracy of a proper Biometric Identification and Authentication Systems in Image Forensics depends on the image quality to arrive at a reliable and accuracy result. To get a noise-free fingerprint image, they are applied under the pre-processing and filtering tasks. The Fingerprint Recognition system is often demanded by the accuracy factor. In this paper an attempt is made to evaluate the filtering techniques in the removal of Salt & Pepper Noise. This work proposes a faster and an efficient way to remove salt-and-pepper impulse noise and also the edge-preserving regularization of the henceforth obtained finger print noise free image. In this paper, we propose a two phase mechanism where the noisy pixels are identified and removed in the first phase and only these noisy pixels are involved in cardinal spline edge regularization process in the second phase. Promising results were found even for Noise levels as high as 90% with the proposed algorithm. The results were found to be much better than the previously proposed nonlinear filters or regularization methods both in terms of noise removal as well as edge regularization for image forensics.
KeywordsImage Forensics Digital Finger Print Images Edge-preserving regularization salt-and-pepper impulse noise cardinal splines
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