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Signature recognition

About: Signature recognition is a research topic. Over the lifetime, 2138 publications have been published within this topic receiving 37605 citations.


Papers
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Proceedings ArticleDOI
03 Aug 2003
TL;DR: The purpose is to improve the performance of an HMM-based off-line cursive handwriting recognition system by providing it with additional synthetic training data by using a perturbation model for generating synthetic text lines from existing cursively handwritten lines of text produced by human writers.
Abstract: A perturbation model for generating synthetic text lines from existing cursively handwritten lines of text produced by human writers is presented. Our purpose is to improve the performance of an HMM-based off-line cursive handwriting recognition system by providing it with additional synthetic training data. Two kinds of perturbations are applied, geometrical transformations and thinning/thickening operations. The proposed perturbation model is evaluated under different experimental conditions.

96 citations

Journal ArticleDOI
TL;DR: This paper lists the different models proposed in order to characterize the handwriting process and focuses on a representation involving a vectorial summation of lognormal functions: the Sigma-lognormal model.

96 citations

Journal ArticleDOI
TL;DR: A new method for identity verification which uses partitioning using capabilities of fuzzy set theory and development on the basis of them the flexible neuro-fuzzy systems and interpretable classification system for final signature classification is proposed.
Abstract: In this paper we propose a new approach to identity verification based on the analysis of the dynamic signature. Considered problem seems to be particularly important in terms of biometrics. Effectiveness of signature verification significantly increases when dynamic characteristics of the signature are considered (e.g. velocity, pen pressure, etc.). These characteristics are individual for each user and difficult to forge. The effectiveness of the verification on the basis of an analysis of the dynamics of the signature can be further improved. A well-known way is to consider the characteristics of the signature in the sections called partitions. In this paper we propose a new method for identity verification which uses partitioning. Partitions represent time moments of signing of the user. In the classification process the partitions, in which the user created more stable reference signatures during acquisition phase, are more important. Other important features of our method are: using capabilities of fuzzy set theory and development on the basis of them the flexible neuro-fuzzy systems and interpretable classification system for final signature classification. In this paper we have included the simulation results for the two currently available databases of dynamic signatures: free SVC2004 and commercial BioSecure database.

95 citations

Journal ArticleDOI
01 Jun 2016
TL;DR: A new algorithm for the dynamic signature verification that implements a new way of signatures division - hybrid partitioning with the possibility of selecting and processing of hybrid partitions in order to increase a precision of the test signature analysis.
Abstract: Graphical abstractDisplay Omitted HighlightsWe propose a new algorithm for the dynamic signature verification.The algorithm implements a new way of signatures division - hybrid partitioning.Hybrid partitions are associated with time and dynamics of the signing process.The algorithm compares test signatures to the reference ones in interpretable way.The algorithm works independently for each signer. Identity verification based on authenticity assessment of a handwritten signature is an important issue in biometrics. There are many effective methods for signature verification taking into account dynamics of a signing process. Methods based on partitioning take a very important place among them. In this paper we propose a new approach to signature partitioning. Its most important feature is the possibility of selecting and processing of hybrid partitions in order to increase a precision of the test signature analysis. Partitions are formed by a combination of vertical and horizontal sections of the signature. Vertical sections correspond to the initial, middle, and final time moments of the signing process. In turn, horizontal sections correspond to the signature areas associated with high and low pen velocity and high and low pen pressure on the surface of a graphics tablet. Our previous research on vertical and horizontal sections of the dynamic signature (created independently) led us to develop the algorithm presented in this paper. Selection of sections, among others, allows us to define the stability of the signing process in the partitions, promoting signature areas of greater stability (and vice versa). In the test of the proposed method two databases were used: public MCYT-100 and paid BioSecure.

95 citations

Patent
04 Dec 2001
TL;DR: In this paper, the authors present a system and a method of validating an identity of a user using a pointing device by comparing a sampled mouse signature with an authenticated mouse signature.
Abstract: The present invention includes a system and a method of validating an identity of a user using a pointing device by comparing a sampled mouse signature with an authenticated mouse signature. The method includes presenting a virtual pad including a background graphic image, a plurality of objects positioned on the background graphic image to a user. The user moves the pointing device to manipulate a cursor on the background graphic image. The method includes a step of sampling a plurality of events corresponding to positions of the cursor to provide a sampled mouse signature including a set of position vectors. The present invention includes comparing the sampled mouse signature to a stored mouse signature representing the identity of a user, and validating the identity of a user in response to the comparing step.

94 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202310
202219
202122
202028
201925
201832