2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) 2017
DOI: 10.1109/icdar.2017.40
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Complexity-Based Biometric Signature Verification

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

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Cited by 4 publications
(5 citation statements)
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“…It involves dividing the entire problem into several sub problems depending on the complexity of the signatures being questioned and developing different strategies for each complexity level. This proposal is reasonable, as it is well known that the quality of forgeries depends on the complexity of the signature, among other properties [9], [59], [60], [61], [62], [63].…”
Section: Methods 3: Feature-distance Matrix With Complexity Methodsmentioning
confidence: 93%
See 1 more Smart Citation
“…It involves dividing the entire problem into several sub problems depending on the complexity of the signatures being questioned and developing different strategies for each complexity level. This proposal is reasonable, as it is well known that the quality of forgeries depends on the complexity of the signature, among other properties [9], [59], [60], [61], [62], [63].…”
Section: Methods 3: Feature-distance Matrix With Complexity Methodsmentioning
confidence: 93%
“…In [66] the authors propose to take into account the signature lengths, the number of pronounced directional changes in the line, or overwritings, the length of the pen-downs and complex pen patterns. However, quantifying the complexity in signatures remains an open challenge [50], although significant advances have been recently made for on-line signatures [61], [62], [63].…”
Section: Methods 3: Feature-distance Matrix With Complexity Methodsmentioning
confidence: 99%
“…Number of strokes/lognormals [83,248], * mathematical transformations (Wavelet [98,200,202,203], * Radon [268], * fractal [84], ** or others like total number, mean, and maximum of intra-/interstroke intersections, the number of x-axes, zero-crossings and the signature length [81,91,93,154,202,246,250]*), symbolic representation [7], * code vectors [234], * Sigma-lognormal based [83,102], * ...…”
Section: -Global Parametersmentioning
confidence: 99%
“…A complete framework for statistical assessment of signature complexity has been also defined. This is based on static and dynamic features, for example, the number of strokes (defined in terms of lognormals in [248]), the total number of intra-/interstroke intersections, the means of intra-/interstroke intersections, the maximum of intra-/interstroke intersections, the number of x-axis intersections, the sums of the horizontal and vertical components of the velocity and acceleration at zero-crossings, and the signature length [154].…”
Section: Stability and Complexitymentioning
confidence: 99%
“…as a motivation for our study. A preliminary version of the proposed signature complexity approach was introduced in [16]. In that study only the pen stylus scenario was considered through the Biose-curID database [17].…”
Section: Introductionmentioning
confidence: 99%