Open AccessProceedings Article
Off-line signature verification based on modified dynamic time warping algorithm
Tian Wei,Lv Jing-Yuan +1 more
- pp 3938-3941
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TLDR
This work presents an innovative approach for off-line signature verification based on modified dynamic time warping (DTW) algorithm using the projection profiles of signatures which acted as weighted DTW, in order to prevent minimum distance distortion caused by outliers.Abstract:
This work presents an innovative approach for off-line signature verification based on modified dynamic time warping (DTW) algorithm. Conventional DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point, By using the projection profiles of signatures, the scheme employed Projection stability Point and Projection stability factor which acted as weighted DTW, in order to prevent minimum distance distortion caused by outliers. The databases of English signatures are applied to the experiments and the average error rates of 11.4% are obtained to verify the effectiveness of the proposed system.read more
References
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Proceedings ArticleDOI
Off-line signature verification using HMM for random, simple and skilled forgeries
TL;DR: The experiments have shown that the error rates of the simple and random forgery signatures are very closed, and this reflects the real applications in which the simple forgeries represent the principal fraudulent case.
Journal ArticleDOI
A comparison of SVM and HMM classifiers in the off-line signature verification
TL;DR: A comparison of the two classifiers in off-line signature verification using random, simple and simulated forgeries to observe the capability of the classifiers to absorb intrapersonal variability and highlight interpersonal similarity.
Journal ArticleDOI
Off-line signature verification based on geometric feature extraction and neural network classification
Kai Huang,Hong Yan +1 more
TL;DR: The role of signature shape description and shape similarity measure is discussed in the context of signature recognition and verification and the proposed method allows definite training control and at the same time significantly reduces the number of enrollment samples required to achieve a good performance.
Journal ArticleDOI
Off-line signature verification and forgery detection using fuzzy modeling
TL;DR: A novel approach to the problem of automatic off-line signature verification and forgery detection based on fuzzy modeling that employs the Takagi-Sugeno (TS) model is proposed, finding that TS model with multiple rules is better thanTS model with single rule for detecting three types of forgeries.
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