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Online signature verification using segmented local features

Authors: Madiha Tahir; M. Usman Akram; Muhammad Arslan Idris;

Online signature verification using segmented local features

Abstract

Biometric is a reliable system that provides person's authentication and verification using his physical and behavioral characteristics. Most of the previous work has been done on online signature verification involved statistical local and global features extracted from x, y coordinates and pen's pressure. Pen's positions along the time series has not used for verification yet. This motivates us to design an efficient online signature verification system by analyzing Local features consists of x, y coordinates and pen's ups and downs. Features are selected using segmentation such that characteristics of the shape of the signature remain maintained. Euclidean distance and dynamic time warping (DTW) are used for enrollment and matching of questioned sample with reference samples. Proposed method is evaluated on Japanese Online test set from ICDAR2013. System's performance is evaluated by computing EER, FAR, FRR, accuracy and time in seconds. We achieved 78.14% accuracy with average elapsed time of 0.13s using segmentation and 78.57% without segmentation with average elapsed time of 3.42s.

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    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Top 10%
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