Off-Line Signature Authentication Based on Moment Invariants Using Support Vector Machine

Radhika, .

doi:10.3844/jcssp.2010.305.311

Cited by 12 publications

(5 citation statements)

References 20 publications

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“…Radhika et al (2010), Zhang (2010, Bertolini et al (2010), Tselios et al (2012), Guerbai et al (2015), Vargas et al (2011), Kumar et al (2012), Pal, U., Pal, S. y Blumenstein (2013), Ferrer et al (2012 Los métodos de clasificación mayormente usados en los trabajos revisados son basados en SVM, superando largamente a los otros métodos, tal como ilustra la tabla 4.…”

Section: Híbridosunclassified

Revisión de algoritmos de verificación automática de firmas off-line

Vílchez-Fernández

2017

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ResumenEn la actualidad, la firma es uno de los distintivos más aceptados para la identificación personal. Su inclusión es obligatoria en documentos como cheques bancarios, contratos, tarjetas de crédito, entre otros documentos públicos y privados. No obstante, la firma se ha convertido en un atractivo objetivo para las falsificaciones y, en consecuencia, para el fraude. Por esta razón, se han realizado investigaciones en soluciones automatizadas de reconocimiento de firmas y estudios del estado del arte que ahora resulta necesario actualizar, puesto que el trabajo más exhaustivo data del 2008 y en los años siguientes se han efectuado nuevas investigaciones. El presente trabajo se enfoca en el estudio comparativo de las técnicas de verificación de firmas off-line desde los puntos de vista de eficiencia y exactitud para verificar la autenticidad de la persona. La metodología de investigación utilizada considera el procedimiento propuesto por Kitchenham, el cual ha sido adaptado e involucra las fases de planeamiento, desarrollo y reportes de la revisión. Palabras clave: Verificación de firmas / reconocimiento de firmas / firmas off-line AbstractNowadays, the signature is one of the most accepted badges for personal identification. Its inclusion is mandatory in documents such as bank checks, contracts, credit cards, among other public and private documents. However, the signature has become an attractive target for counterfeiting and, consequently, for fraud. For this reason, research has been carried out on automated signature recognition and state-of-the-art studies that are now required to be updated, since the most comprehensive work dates back to 2008 and in the following years further research has been carried out. The present work focuses on the comparative study of verification techniques of signatures off-line from the point of view of efficiency and accuracy to verify the person's authenticity. The research methodology used considers the procedure proposed by Kitchenham, which has been adapted, and involves the phases of planning, development and reporting of the review.

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Section: Híbridosunclassified

Revisión de algoritmos de verificación automática de firmas off-line

Vílchez-Fernández

2017

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“…The unavoidable side-effect of the signatures is that they can be misused for the purpose of the feigning a data authenticity. Hence, the requirement for the examination in wellorganized automatic resolutions for the signature recognition and confirmation has improved in later years for the purpose of avoiding the risk of fraud [2][3][4][5]. In signature confirmation, forged signatures can be cracked up into the three various classes.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Offline Signature Verification System

Yadav¹,

Tyagi²

2015

IJSIA

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A digital signature is a mathematical structure for indicating the validity of digital information or any document. A message is created by a known sender whose digital signature provides a recipient reason, such that the sender cannot reject having sent the message confirmation and that the message was not changed in transportation integrity. The Signature recognition and verification are a behavioral biometric. It can be operated in two various types: one is the Off-Line or Static Signature Verification Technique and another is the On-line or Dynamic Signature Verification Technique. In this paper, we are studying about Off-Line or Static Signature Verification Technique. In this method, users write their own signature on the blank paper and then digitize it with an optical scanner or a camera, and then the biometric system identifies the signature by analyzing its shape and this collection is also called as "off-line" Signature verification. Signature authentication can be divided into three main classes. These classes are based on how alike a forgery is in relation to signature and are identified as random, simple and skilled. In the random forgery the forger does not know about the signer's shape or signature name. In the simple forgery or unskillful forgery, the forger knows the name of the actual signer but don't know how his signature looks like. And in the skilled forgery, the forger knows both the information of the signer.

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“…The unavoidable side-effect of the signatures is that they can be misused for the purpose of the feigning a data authenticity. Hence, the requirement for the examination in well-organized automatic resolutions for the signature recognition and confirmation has improved in later years for the purpose of avoiding the risk of fraud [2][3][4][5]. In signature confirmation, forged signatures can be cracked up into the three various classes.…”

Section: Introductionmentioning

confidence: 99%