Abstract
In this paper, we propose a concavity and convexity enhancement method for noiseless binarization of fingerprint images as a preprocessing step during authentication. Personal authentication with fingerprints is vital and reliable in biometrics based recognition. However, noises could be introduced in fingerprint images capturing, which makes feature extraction and authentication very challenging. Recently, due to the increased need for personal authentication, fingerprint recognition has been widely used in the media. In fingerprint processing, a scanner is usually used to collect the fingerprints. During capture, noise is introduced into the fingerprint image. It is therefore important that preprocessing is carried out, because there are variations in brightness, contrast and noise. To overcome the issues, our proposed method binarizes the fingerprint images. Furthermore, the proposed method produces better results than discriminant analysis or local thresholds methods. Computer Simulations were then carried out to show the effectiveness of the proposed technique. A binarization accuracy of 97.5% was achieved. In authentication, we achieved a perfect False Rejection and False Acceptance Rate of 0.6172%.
