Abstract

Fingerprint identification is one of the oldest and popularly used forms of biometric identification system. Fingerprint image quality is of much importance to achieve high performance in Automatic Fingerprint Identification System (AFIS). Most of the fingerprint Recognition system relies on fingerprint ridges to extract the features. The fingerprint images which are corrupted due to variations in skin and impression conditions may reduce the efficiency of the feature extraction module. Therefore an efficient and a robust fingerprint image denoiser is necessary to overcome the challenges faced by the existing techniques. In this paper a new fingerprint image denoiser based on wavelets and contrast based grouping is proposed. The proposed model is compared with the existing algorithms. Experimental results proved that the proposed model is efficient in denoising the fingerprint image.

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