In this paper we propose a new Handwritten Signature Authentication Scheme. The scheme consists of two main Rule Set Algorithms and one Authentication Algorithm. The Algorithms are based on extensive statistical analysis, Mean Variance and Theory of Estimation. This is an extension work of Handwritten Signature Identification. This scheme supports the application environment and we strongly believe that "User Authentication" could be a solid platform for future research and study. © 2008 IEEE.

S K BANDYOPADHYAY

D BHATTACHARYYA

P DAS

D DEBNATH

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Handwritten Signature Authentication Using Statistical Estimation

Proceedings - 2008 International Conference on Multimedia and Ubiquitous Engineering, MUE 2008

Humans are comfortable with pen and papers for authentication and authorization in legal transactions. In this case it is very much essential that a person's Hand written signature to be identified uniquely. The development of efficient technique is to extract features from Handwritten Signature Image and verify the signature with higher accuracy. This paper presents a method for off line hand written signature verification with higher accuracy. In this paper we have introduced a procedure to extract features from Handwritten Signature Images. That computed feature is used for verification. Here we used a clustering technique for verification. © 2010 Springer-Verlag.

Communications in Computer and Information Science

Extraction of features from signature image and signature verification using clustering techniques

Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems

Picture ID Authentication Using Invisible Watermark and Facial Recognition Features

Proceedings of the IEEE

Image authentication techniques for surveillance applications

Handwritten signature authentication using statistical estimation

Journal	Proceedings - 2008 International Conference on Multimedia and Ubiquitous Engineering, MUE 2008
Publisher	-