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Related Experiment Video

Updated: Apr 19, 2026

Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

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Online Signature Verification Based on DCT and Sparse Representation.

Yishu Liu, Zhihua Yang, Lihua Yang

IEEE Transactions on Cybernetics

|December 23, 2014

Summary

This study introduces a new online signature verification method using discrete cosine transform (DCT) and sparse representation. The technique achieves reliable authentication with superior performance compared to existing methods.

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Area of Science:

Computer Science
Biometrics
Pattern Recognition

Background:

Online signature verification is crucial for identity authentication.
Existing methods face challenges with time series of varying lengths.

Purpose of the Study:

To propose a novel online signature verification technique.
To leverage discrete cosine transform (DCT) and sparse representation for enhanced accuracy.

Main Methods:

A new DCT property is utilized for compact signature representation and energy feature extraction.
Sparse representation is applied with a novel task-specific dictionary construction for sparsity feature extraction.
Energy and sparsity features are concatenated into a comprehensive feature vector.

Main Results:

The proposed method demonstrates reliable person authentication.
Experimental results on SUSIG-Visual and SVC2004 databases show superior verification performance over state-of-the-art techniques.

Conclusions:

The combined DCT and sparse representation approach offers an effective solution for online signature verification.
The method provides a robust alternative for handling variable-length time series data in biometrics.