- Title
- Fingerprint feature extraction and classification by learning the characteristics of fingerprint patterns
- Creator
- Kulkarni, Siddhivinayak
- Date
- 2012
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/44729
- Identifier
- vital:4551
- Identifier
- http://www.scopus.com/inward/record.url?eid=2-s2.0-79960894811&partnerID=40&md5=f643b73b81abde63ef8bf5975006fc51
- Identifier
- ISSN:1210-0552
- Abstract
- This paper presents a two stage novel technique for fingerprint feature extraction and classification. Fingerprint images are considered as texture patterns and Multi Layer Perceptron (MLP) is proposed as a feature extractor. The same fingerprint patterns are applied as input and output of MLP. The characteristics output is taken from single hidden layer as the properties of the fingerprints. These features are applied as an input to the classifier to classify the-features into five broad classes. The preliminary experiments were conducted on small benchmark database and the found results were promising. The results were analyzed and compared with other similar existing techniques. © ICS AS CR 2011.
- Relation
- Neural Network World Vol. 21, no. 3 (2012), p. 219-226
- Rights
- ICS AS CR
- Rights
- This metadata is freely available under a CCO license
- Subject
- Artificial neural networks; Biometrics; Feature extraction; Fingerprints; Multi Layer Perceptron; Benchmark database; Feature extractor; Fingerprint features; Fingerprint images; Fingerprint pattern; Hidden layers; Input and outputs; Novel techniques; Texture patterns; Two stage; Neural networks
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