Velocity and pressure-based partitions of horizontal and vertical trajectories for on-line signature verification

Authors:
Muhammad Talal Ibrahim;M. Aurangzeb Khan;Khurram Saleem Alimgeer;M. Khalid Khan;Imtiaz A. Taj;Ling Guan
Affiliations:
Ryerson Multimedia Research Lab, Ryerson University, Toronto, Canada;Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan;Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan;Centre for Image Analysis, Uppsala University, Uppsala, Sweden;Department of Electronics Engineering, Mohammad Ali Jinnah University, Islamabad, Pakistan;Ryerson Multimedia Research Lab, Ryerson University, Toronto, Canada
Venue:
Pattern Recognition
Year:
2010

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Abstract

In general, shape of an on-line signature is used as a single discriminating feature. Sometimes shape of signature is used alone for verification purposes and sometimes it is used in combination with some other dynamic features such as velocity, pressure and acceleration. The shape of an on-line signature is basically formed due to the wrist and fingers movements where the wrist movement is represented by the horizontal trajectory and the movement of the fingers is represented by vertical trajectory. As the on-line signature is formed due to the combination of two movements that are essentially independent of each other, it will be more effective to use them as two separate discriminating features. Based on this observation, we propose to use these trajectories in isolation by first decomposing the pressure and velocity profiles into two partitions and then extracting the underlying horizontal and vertical trajectories. So the overall process can be thought as the process which exploits the inter-feature dependencies by decomposing signature trajectories depending upon pressure and velocity information and performs verification on each partition separately. As a result, we are able to extract eight discriminating features and among them the most stable discriminating feature is used in verification process. Further Principal Component Analysis (PCA) has been proposed to make the signatures rotation invariant. Experimental results demonstrate superiority of our approach in on-line signature verification in comparison with other techniques.