On-Line Signature Verification by Dynamic Time Warping and Gaussian Mixture Models

Miguel-Hurtado, Oscar; Mengibar-Pozo, L.; Lorenz, Michael G.; Liu-Jimenez, Judith

doi:10.1109/ccst.2007.4373463

Cited by 35 publications

(11 citation statements)

References 8 publications

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“…It is clear from the results that our proposed system performs better even if training is done by using only 3 and 5 genuine signatures. The results on the MCYT database is also satisfactory where we have achieved the EER of .0020 when only 3 genuine signatures were used for training and EER of .0008 when only 5 genuine signatures were used, where as average EER in [13] and [9] is 0.0120, 0.0375 with 5 training signatures respectively. …”

Section: Experimental Results and Conclusionsupporting

confidence: 55%

On-line Signature Verification Using Most Discriminating Features and Fisher Linear Discriminant Analysis (FLD)

Ibrahim

Kyan

Guan

2008

2008 Tenth IEEE International Symposium on Multimedia

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In this work, we employ a combination of strategies for partitioning and detecting abnormal fluctuations in the horizontal and vertical trajectories of an On-line generated signature profile. Alternative partitions of these spatial trajectories are generated by splitting each of the related angle, velocity and pressure profiles into two regions representing both high and low activity. The overall process can be thought of as one that exploits inter-feature dependencies by decomposing signature trajectories based upon angle, velocity and pressure -information quite characteristic to an individual's signature. In the verification phase, distances of each partitioned trajectory of a test signature are calculated against a similarly partitioned template trajectory for a known signer. Finally, these distances become inputs to Fisher's Linear Discriminant Analysis (FLD). Experimental results demonstrate the superiority of our approach in On-line signature verification in comparison with other techniques.

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Section: Experimental Results and Conclusionsupporting

confidence: 55%

On-line Signature Verification Using Most Discriminating Features and Fisher Linear Discriminant Analysis (FLD)

Ibrahim

Kyan

Guan

2008

2008 Tenth IEEE International Symposium on Multimedia

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“…DTW based approach by Kholmatov is ranked¯rst for skilled forgeries. The work done by Oscar 23 8 The singular points are used to determine the parameters of the zero-pole model in an o²ine scenario. Our work also uses global information such as acceleration vector in an online scenario.…”

Section: Discussionmentioning

confidence: 99%

A Novel Approach for Authentication of Online Handwritten Signature Based on Residuals, Poles and Zeros

Radhika¹,

Venkatesha²,

Sekhar

2011

Int. J. Patt. Recogn. Artif. Intell.

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This paper proposes an online signature authentication based on polynomial modeling. The derived feature acceleration is used. The order of the polynomial is carefully selected for each subject using the acceleration vector. The dynamic warping algorithm and mean squared error measure aid in standard template selection process for a subject. The best¯t order is directly dependent on the cursive information of the signature sample. We provide a practical analysis of residual term, number of zeros inside the unit circle and distance measure on pole values for the purpose of classi¯cation. Storing order and standard template for a subject, reduces the runtime and memory requirements for a dynamic system. The best performance was achieved based on the number of zeros inside unit circle with false rejection rate as 5% and false acceptance rate as 7%. The aim of the work is to provide simple robust authentication suitable for hand held devices. Even compared to state-of art experiments, the proposed system is aimed to provide authentication using a single derived feature.

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“…The offered way does not deny the existing verification methods (Kamel, et al, 2008), (Impedovo, & Pirlo, 2008), (Fabregas, Faundez-Zanuy, 2009), (Miguel-Hurtado, et al, 2007), it is an additional alternative when determining the results of the signature recognition.…”

Section: Resultsmentioning

confidence: 99%

“…9, No. 1;2015 We shall find the value of threshold for decision-making proceeding from the balance between sensitivity and specificity. According to the chosen value of threshold magnitudes of errors of first and second kind are defined for the signature verification.…”

Section: Resultsmentioning

confidence: 99%

About One Method of On-Line Signature Verification Using Radial Basis Function

Anisimova¹,

Ibatullin²

2014

MAS

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The article is devoted to the study of a possibility of on-line signature verification using the wavelet transform with the radial basis function. Representation of the signature in the form of function, invariant concerning a position, -the signature is replaced by a broken curve and is described using the angles between the adjacent links -is offered. Using the wavelet transforms for the signature description, comparison of expansion coefficients of functions of signatures by the radial basis function to verify signatures is described in detail. In the result of application of the offered method the magnitude of error of first kind has made 4.4%, the magnitude of error of second kind -2.8%.

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On-Line Signature Verification by Dynamic Time Warping and Gaussian Mixture Models

Cited by 35 publications

References 8 publications

On-line Signature Verification Using Most Discriminating Features and Fisher Linear Discriminant Analysis (FLD)

On-line Signature Verification Using Most Discriminating Features and Fisher Linear Discriminant Analysis (FLD)

A Novel Approach for Authentication of Online Handwritten Signature Based on Residuals, Poles and Zeros

About One Method of On-Line Signature Verification Using Radial Basis Function

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