Biometrics and Bioinformatics

R. Vinothkanna ¹, C. T. Subash ¹

Affiliations
1 IT Department, Tamilnadu College of Engineering, Coimbatore-641659, IN

Abstract

Fingerprint authentication remains as one of the most prominent biometric identification methods. In this paper, we propose to use the fingerprint valley instead of ridges for the Binarization and Thinning process to extract fingerprint valley minutiae, because lots of research has done on ridges not on valleys. We first use several preprocessing steps on the binary image in order to eliminate the spurious lakes and dots, and to reduce the spurious islands, bridges, and spurs in the skeleton image. By removing all the bug pixels introduced at the thinning stage, our algorithm can detect a maximum number of minutiae from the fingerprint skeleton using the Gabor filter. This allows the true minutiae preserved and false minutiae removed in post processing stages. Gabor filter has also given lots of best results on ridges extraction. So we tried gabor filter for valley extraction and we got number of minutiae extracted differs from ridges to valleys. The proposed method saves memory space, and also speeds up the whole procedure.

Keywords

Biometrics, Bug Pixel, Fingerprint Minutiae Extraction, Gabor Filter, Valleys.

Full Text

     

R. Vinothkanna ¹, T. Pavitha ²

Affiliations
1 Department of Information Technology, Tamilnadu College of Engineering, Coimbatore, IN
2 Tamilnadu College of Engineering, Coimbatore, IN

Abstract

Biometrics is the science and technology of authentication by identifying the living individual's physiological or behavioral attributes. Fingerprint identification is one of the most well known and published biometrics. Fingerprints have been used for identification for over a century, more recently becoming automated due to advancement in computing capabilities and their uniqueness and consistency over time and access control.In Pre-processing stage, notch filter is used for fast enhancement and found to be best. In traditional cryptographic systems, one or more keys are used to convert the plaintext (i.e. data to be encrypted) to cipher text (i.e. encrypted data). The encrypting key(s) maps the plain text to essentially a sequence of pseudo random bits (modern crypto algorithms are designed with this criteria), that can only be mapped back to the plain text using the appropriate decrypting key(s). Here, the plain text can be any data that needs to be stored or transmitted securely:financial transactions, E-mail communication, records, fingerprint images, secret cryptographic keys, etc. The proposed method has a excellent capability both in filtering effectiveness and efficiency.

Keywords

Biometrics, Encryption, Feature Extraction, Filter, Fingerprints, Preprocessing.

Full Text