| Offline Handwritten Signature Verification Based on Circlet Transform and Statistical Features |
| Paper ID : 1047-MVIP2020 |
| Authors: |
|
Atefeh Foroozandeh *1, Ataollah Askari Hemmat2, Hossein Rabbani3 1none,none 2Department of Applied Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman 3Department of Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences |
| Abstract: |
| Handwriting signatures are widely used to register ownership in banking systems, administrative and financial applications, all over the world. With the increasing advancement of technology, increasing the volume of financial transactions, and the possibility of signature fraud, it is necessary to develop more accurate, convenient, and cost effective signature based authentication systems. In this paper, a signature verification method based on circlet transform and the statistical properties of the circlet coefficients is presented. Experiments have been conducted using three benchmark datasets: GPDS synthetic and MCYT-75 as two Latin signature datasets, and UTSig as a Persian signature dataset. Obtained experimental results, in comparison with literature, confirm the effectiveness of the presented method. |
| Keywords: |
| Offline Handwritten Signature Verification, Circlet Transform, Gray Level Co-occurrence Matrix, Statistical Feature |
| Status : Paper Accepted (Oral Presentation) |
