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MA Shi-liang

Bio: MA Shi-liang is an academic researcher. The author has contributed to research in topics: Signature (logic) & Signature recognition. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Papers
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Journal Article
TL;DR: This paper presents a stroke-matching algorithm of handwritten signature verification that is effectual to be examined by signature data from SVC 2004, and introduces distance calculation formula based on weighting H′ module to calculate the difference between input signatures and true signatures.
Abstract: On-line signature handwritten verification is a topic in the field of biometric authentication nowBy comparing the picture,stroke,speed and pressure of input signaturs with genuine signatures in database,the computer can distinguish the true or false of a handwritten signature real-timelyStroke-matching and result judgment are the keys to this problemThis paper presents a stroke-matching algorithm of handwritten signature verificationThe algorithm is effectual to be examined by signature data from SVC 2004(First International Signature Verification Competition)The FRR(False Reject Ratio) is 20% and all forgeries are rejectedThe paper also introduces distance calculation formula based on weighting H′ module to calculate the difference between input signatures and true signaturesOn-line signature handwritten verification is very convenient,quick-made,suitable to verification and its effectiveness has been illustrated by practical examples

2 citations


Cited by
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Journal ArticleDOI
TL;DR: An online handwritten signature verification algorithm using improved DTW is presented and the result of experiment proves that this algorithm obtains a good verification effect.
Abstract: Online handwritten signature verification is widely used because of its celerity and convenience. It is the personal verification based on biometrics technology. It is the verification using information about the movement during writing signature, so it becomes an accepted method of personal verification. Basing on this thesis, an online handwritten signature verification algorithm using improved DTW is presented. The weak point of classic DTW is that only the data points by warping the x-axis are considered but the differences on y-axis of two series are not considered. The two situations above are considered in the improved DTW method in order to prevent this problem and the distance measure of DTW is modified based on improved DTW in this paper particularly. The result of experiment proves that this algorithm obtains a good verification effect.

9 citations

Proceedings ArticleDOI
12 Dec 2011
TL;DR: A new method fusing multi-biometric features base on PCA is proposed in this paper and performs much better on this dataset when the EER (Equal Error Rate) is 1%.
Abstract: The recognition based on Fusing Multi-Biometrics is a hot point in authentications. A new method fusing multi-biometric features base on PCA is proposed in this paper. At first, the features are extracted from the voice, face images and online handwritings of one person. Then, three features are fused by the means of PCA method. Finally, the authorization is implemented through classification by minimizing the Euclidean distance of different people. The dataset we built includes the voice, face image and online handwritings of 20 volunteers. Our method performs much better on this dataset when the EER (Equal Error Rate) is 1%.

4 citations