Fingerprint feature extraction and classification by learning the characteristics of fingerprint patterns

Title:

Fingerprint feature extraction and classification by learning the characteristics of fingerprint patterns

Creator:

Kulkarni , Siddhivinayak

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:5d7703c4-5641-46c3-b6e4-62fccf8b185c
uuid:5d7703c4-5641-46c3-b6e4-62fccf8b185c
doi:10.14311/NNW.2011.21.013

Subject:

Biometrics, multi layer perceptron, artificial neural networks, fingerprints, and feature extraction

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2011 Volume:21 | Number:3

Harvested from:

CDK

Metadata only:

false