Abstract
A Novel Approach to Dynamic Signature Verification Using Sensor-Based Data glove
Highlights
In early days, human beings were commonly Signature recognition belongs to this last category and identified by their names
The SVD-signature verification algorithm is written in MATLAB 7.0 and run on a machine powered by Intel Core 2 Dual processor
Our proposed technique achieved accuracy with 2.46, 3.6 and 5.0% of Equal Error Rate (EER) using 14, 5 and 4 sensor based data glove, which is comparable with other dynamic signature verification techniques and it is promising for future applications of dynamic signature verification techniques
Summary
Human beings were commonly Signature recognition belongs to this last category and identified by their names. The. SIGNATURE RECOGNITION problem of personal identification is multiplied when computer comes into the communication channel of two parties. SIGNATURE RECOGNITION problem of personal identification is multiplied when computer comes into the communication channel of two parties In on-line mode, users write their signature in technology These methods have major a digitizing tablet such as the device[5], which acquires drawbacks as passwords and PINs tend to be forgotten the signature in real time. Another possibility is the or shared out whereas token can be lost or stolen. People recognition by means of biometrics[1,2,3] can be split into two main categories: a) Passive or Physiological biometrics such as face recognition, fingerprint, iris or retina, hand geometry, off-line hand signature and DNA (Deoxyribonucleic Acid) analysis
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