• Corpus ID: 86584904

Static Signature Authentication based on J48 and Random Forest

@article{Singh2017StaticSA,
  title={Static Signature Authentication based on J48 and Random Forest},
  author={Ranjan Kumar Singh and Sushila Maheshkar and Vikas Maheshkar},
  journal={International journal of engineering research and technology},
  year={2017},
  volume={6}
}
With the exposure and development of technology, a better security system is needed to protect the data. Off-line signature verification is one of the prime area of research which is most widely recommended by the research community for security issues. For the Off-line signature verification from spontaneous handwritten signature image a precise and effective method is proposed which contributes significantly to that area and comprises of image prepossessing, feature extraction and decision… 
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The method presented in this paper consists of image prepossessing, geometric feature extraction, neural network training with extracted features and verification, which includes applying the extracted features of test signature to a trained neural network which will classify it as a genuine or forged.

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