Abstract
Fingerprint recognition is a mature biometric technique for identification or authentication application. In this work, we describe a method based on the use of neural network to authenticate people who want to accede to an automated fingerprint system for E-learning. The idea is to apply back propagation algorithm on a multilayer perceptron during the training stage. One of the advantages of this technique is the use of a hidden layer which allows the network to make comparison by calculating probabilities on template which are invariant to translation and rotation. Results come both from the NIST special database 4 and a local database, and show that a proposed method gives good results in some cases.
Highlights
IntroductionUsual identification methods based on what we have (magnetic card, identity card, chip, etc.) or on what we know (password, encoding, etc.) cause big problems of reliability [1] [2]
Usual identification methods based on what we have or on what we know cause big problems of reliability [1] [2]
International NIST database 4 which is a specific database for fingerprint recognition; it consists of 2000 pairs of fingerprint images in the format 512 × 512 with 8-bit grayscale [21]
Summary
Usual identification methods based on what we have (magnetic card, identity card, chip, etc.) or on what we know (password, encoding, etc.) cause big problems of reliability [1] [2]. The recent terrorist acts and threats to many countries, coupled with the growing evolution of cybercrime in a world where all tasks tend to become automatic identification/authentication of flawless natural persons have become a problem crucial for security reasons (border controls, access to public or virtual sites, transport, ...). All these problems have encouraged the further development of biometrics as an identification and authentication tool. The use of fingerprints is one of the oldest and most successful methods of identification/authentication biometrics [3] [4]. Galton was the first to prove the existence of the papillary drawings from birth to death [5]; this particular arrangement of the papillary lines forms points called minutiae, which are the cause of uniqueness and
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More From: Journal of Intelligent Learning Systems and Applications
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