Devnagari Handwritten Signature Recognition Using Neural Network - Dewangan, Shailendra Kumar
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Handwritten signatures are considered as the most natural method of authenticating a person's identity as compared to other biometric and cryptographic forms of authentication. The learning process inherent in Neural Networks can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This work presents a method for verifying handwritten signatures by using Neural Networks architecture. Various features of signature such as height, length, slant, moment etc. are extracted and used to train the Network.

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Produktbeschreibung
Handwritten signatures are considered as the most natural method of authenticating a person's identity as compared to other biometric and cryptographic forms of authentication. The learning process inherent in Neural Networks can be applied to the process of verifying handwritten signatures that are electronically captured via a stylus. This work presents a method for verifying handwritten signatures by using Neural Networks architecture. Various features of signature such as height, length, slant, moment etc. are extracted and used to train the Network.
Autorenporträt
Shailendra Kumar Dewangan is an Assistant Professor in the Department of Electronics & Instrumentation Engg. at CSIT Durg, Chhattisgarh, India. His areas of interest include Digital Signal Processing & advancements in communication technology. He has published multiple articles in various International and National Journals & Conferences.