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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 4, ISSUE 10, OCTOBER 2015

Biometric system based on off-line signatures

Bhanu Priya Taneja, Navdeep Kaur

DOI: 10.17148/IJARCCE.2015.41022

Abstract: This paper discusses the process of off line signature recognition and verification system using neural networks. The paper consists of two stages 1) Evaluating feature vectors of off line-signature images. 2) Training and Validation using back-propagation artificial neural network. Three layer feed forward MLP classifier have been used for pattern recognition process. The main advantage of feed forward neural network is that they are easy to use, and that they can approximate any input/output mapping with weights and thresholds (biases) of the model. Different stages of the process are explained in the paper by making use of proper algorithms. The overall accuracy achieved is 96.3%.



Keywords: Confusion matrix, Feed forward neural network, Kurtosis, Receiver operating characteristics (ROC).

How to Cite:

[1] Bhanu Priya Taneja, Navdeep Kaur, “Biometric system based on off-line signatures,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2015.41022