A New approach for Finger-Print Identification
The choice of an object representation is crucial for the effective performance of cognitive tasks such as fingerprint image (FPI) recognition, this is because how robustly and efficiently Recognition tasks can be performed depends on the choice of the feature representation. This paper introduces radon transform coefficients as an effective and efficient FPI representation. The radon represent FPI with sets of weighted coefficients that are specially chosen to reflect the properties of the represent FPI.The radon transformer parameters are chosen according to a specific discrete scheme that is based on the discrete Multiwvelet transform. In this paper, we describe a new method to identify fingerprint by combining an extreme classifying method, SVM, and radon transformer-based technique. This approach is a learning method whose identifying time is so fast while training time is acceptable.
Keywords: Fingerprint identification, FPI , support vector machine, and radon transformers
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ABOUT THE AUTHORS
Attallah Bilal
LSSD Laboratory, Electronic Department USTO, Oran 31000, Algeria
Hendel Fatiha
LSSD Laboratory, Electronic Department USTO, Oran 31000, Algeria
Boudjelal Abdelwahhab
Electronic Department University of M'sila, M'sila 28000, Algeria
Attallah Bilal
LSSD Laboratory, Electronic Department USTO, Oran 31000, Algeria
Hendel Fatiha
LSSD Laboratory, Electronic Department USTO, Oran 31000, Algeria
Boudjelal Abdelwahhab
Electronic Department University of M'sila, M'sila 28000, Algeria
