The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of COMPUTERS AND COMMUNICATIONS
Transactions ID Number: 19-803
Full Name: Debnath Bhattacharyya
Position: Professor
Age: ON
Sex: Male
Address: Vill. Langalberia, P.O. Gobindopur, Dist. 24-Parganas (South)
Country: INDIA
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E-mail address: debnathb@gmail.com
Other E-mails: debnath@sersc.org
Title of the Paper: Design of Artificial Neural Network for Handwritten Signature Recognition
Authors as they appear in the Paper: Debnath Bhattacharyya, and Tai-hoon Kim
Email addresses of all the authors: debnathb@gmail.com, taihoonn@empal.com
Number of paper pages: 8
Abstract: Numerous approaches have been proposed for Handwritten Signature Identification systems. Various successful domain specific applications using ANN (artificial neural networks) can be found, but not flexible enough for generalization. Besides all, one approach that has shown great promise is the use of ANN in the Handwritten Signature Identification. To avoid forgery and ensure the confidentiality of Information in the field of Information Technology Security an inseparable part of it. In order to deal with security, Authentication plays an important role. This paper presents a view on the signature recognition technique and we also discussed about a technology of Signature Authentication by Back-propagation Algorithm with application. The purpose of this technique is to ensure that the rendered services are accessed only by a legitimate user, and not anyone else. By using this method it is possible to confirm or establish an individual’s identity. In this paper w!
e explore a new recognition technique; an ANN is trained to identify patterns among different supplied handwriting samples. Handwritten signature samples are considered input for our artificial neural network model and typically weights also supplied for recognition.
Keywords: Recognition, Neural network, Signature, Pattern recognition, Authentication, and Security.
EXTENSION of the file: .doc
Special (Invited) Session: Signature Recognition using Artificial Neural Network
Organizer of the Session: 644-160
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IP ADDRESS: 122.160.238.214
