Using geometric extrema for segment-to-segment characteristics comparison in online signature verification

Lee, Jaeyeon; Yoon, Ho-Sub; Soh, Jung; Chun, Byung Tae; Chung, Yun Koo

doi:10.1016/s0031-3203(03)00229-2

Cited by 43 publications

(21 citation statements)

References 19 publications

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“…In order to allow the segmentation of two or more signatures into the same number of perfectly corresponding segments, dynamic time warping (DTW) has been widely used for signature segmentation [55], [166], [172], [275]. After the splitting of a first signature, according to uniform spatial criteria [172] or the position of geometric extremes [55], [166], DTW is applied to determine the corresponding set of points on other specimens.…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

“…After the splitting of a first signature, according to uniform spatial criteria [172] or the position of geometric extremes [55], [166], DTW is applied to determine the corresponding set of points on other specimens. A model-guided segmentation technique has also been proposed [275].…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

“…Some parameters are specifically devoted to dynamic signature verification. This is the case of some global parameters that describe the signature apposition process, as the total signature time duration [146], [147], [170], [266], the pen-down time ratio [146], [147], [227], [335], and the number of pen lifts (pen-down, pen-up) [82], [166], [169], [170]. Other parameters are numerically derived from time functions representative of a signature, like, for instance, the average (AVE), the root mean square (rms), and the maximum (MAX) and minimum (MIN) values of position, displacement, speed, and acceleration [169], [170], [227].…”

Section: Feature Extractionmentioning

confidence: 99%

“…The verification result was achieved by the combination of the information derived by global and local features. Lee et al [166] performed signature segmentation by a DP technique based on geometric extrema. Segment matching was performed by global features and a DP approach.…”

Section: Performance Evaluationmentioning

confidence: 99%

See 3 more Smart Citations

Automatic Signature Verification: The State of the Art

Impedovo

Pirlo

2008

IEEE Trans. Syst., Man, Cybern. C

536

295

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Abstract-In recent years, along with the extraordinary diffusion of the Internet and a growing need for personal verification in many daily applications, automatic signature verification is being considered with renewed interest. This paper presents the state of the art in automatic signature verification. It addresses the most valuable results obtained so far and highlights the most profitable directions of research to date. It includes a comprehensive bibliography of more than 300 selected references as an aid for researchers working in the field.

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Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

Section: Feature Extractionmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

Automatic Signature Verification: The State of the Art

Impedovo

Pirlo

2008

IEEE Trans. Syst., Man, Cybern. C

536

295

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show abstract

“…The importance of a point is determined by the rate of change of the writing angle around it. We can also include in this category techniques based on the detection of geometric extremes [5].…”

Section: Signature Segmentationmentioning

confidence: 99%

Two Bioinspired Methods for Dynamic Signatures Analysis

Canuto

Dorizzi

Montalvão

2013

New Trends in Image Analysis and Processing – ICIAP 2013

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Abstract. This work focuses on the problem of dynamic signature segmentation and representation. A brief review of segmentation techniques for online signatures and movement modelling is provided. Two dynamic signature segmentation/representation methods are proposed. These methods are based on psychophysical evidences that led to the well-known Minimum Jerk Model. These methods are alternatives to the existing techniques and are very simple to implement. Experimental evidence indicates that the Minimum Jerk is in fact a good choice for signature representation amongst the family of quadratic derivative cost functions defined in Section 2.

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Aligning and Segmenting Signatures at Their Crucial Points Through DTW

Quan

2005

Lecture Notes in Computer Science

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Using geometric extrema for segment-to-segment characteristics comparison in online signature verification

Cited by 43 publications

References 19 publications

Automatic Signature Verification: The State of the Art

Automatic Signature Verification: The State of the Art

Two Bioinspired Methods for Dynamic Signatures Analysis

Aligning and Segmenting Signatures at Their Crucial Points Through DTW

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