Handwritten Signature Verification Using Complementary Statistical Models

نویسندگان
چکیده

منابع مشابه

Handwritten Signature Verification Using Complementary Statistical Models

This paper describes a system for performing handwritten signature verification using complementary statistical models. The system analyses both the static features of a signature (e.g., shape, slant, size), and its dynamic features (e.g., velocity, pen-tip pressure, timing) to form a judgment about the signer’s identity. This approach’s novelty lies in combining output from existing Neural Net...

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Handwritten Signature Verification Using Hidden Markov Models

In this paper we present the work developed on offline signature verification using Hidden Markov Models (HMM)[1]. HMM is a well-known technique used by other biometric features, for instance, in speaker recognition and dynamic or on-line signature verification. Our goal here is to extend Left-to-Right (LR)-HMM to the field of static or off-line signature processing using results provided by im...

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Statistical Approach for Offline Handwritten Signature Verification

Signatures were considered an important tool for authenticating the identity of human beings. So, signature verification was one of the biggest uses for that. We proposed an algorithmic approach for the verification of handwritten signatures by applying some statistical methods. The research work was based on the collection of set of signatures from which an average signature was obtained based...

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Online Handwritten Signature Verification Using Hidden Markov Models

Most people are used to signing documents and because of this, it is a trusted and natural method for user identity verification, reducing the cost of password maintenance and decreasing the risk of eBusiness fraud. In the proposed system, identity is securely verified and an authentic electronic signature is created using biometric dynamic signature verification. Shape, speed, stroke order, of...

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Optimizing Handwritten Signature Verification

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ژورنال

عنوان ژورنال: Journal of Computers

سال: 2009

ISSN: 1796-203X

DOI: 10.4304/jcp.4.7.670-680