Fingerprint image preprocessing for robust recognition
Fingerprint is the oldest and most widely used form of biometric identification. Since they are mainly used in forensic science, accuracy in the fingerprint identification is highly important. This accuracy is dependent on the quality of image. Most of the fingerprint identification systems are based on minutiae matching and a critical step in correct matching of fingerprint minutiae is to reliably extract minutiae from the fingerprint images. However, fingerprint images may not be of good quality. They may be degraded and corrupted due to variations in skin, pressure and impression conditions. Most of the feature extraction algorithms work on binary images instead of the gray scale image and results of the feature extraction depends upon the quality of binary image used. Keeping these points in mind, image preprocessing including enhancement and binarization is proposed in this work. This preprocessing is employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations and hence to get a robust matching performance. In this dissertation, we give an introduction to the ngerprint structure and identification system . A discussion on the proposed methodology and implementation of technique for fingerprint image enhancement is given. Then a rough-set based method for binarization is proposed followed by the discussion on the methods for minutiae extraction. Experiments are conducted on real fingerprint images to evaluate the performance of the implemented techniques.
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