A NOVEL AND PRACTICAL SYSTEM FOR VERIFYING SIGNATURES ON PERSIAN HANDWRITTEN BANK CHECKS

Author:

FOROOZANDEH ATEFEH1,AKBARI YOUNES2,JALILI MOHAMMAD J.2,SADRI JAVAD13

Affiliation:

1. Department of Computer Engineering, Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, P.O.Box 97175-615, Iran

2. Department of Computer and IT Engineering Faculty of Engineering, Payame Noor University (Central Branch of Tehran), Tehran, Iran

3. McGill Center for Bioinformatics, School of Computer Science, McGill University, Room 3140, Trottier Building, 3630 University Street, Montreal, Quebec, Canada H3A 2B2, Canada

Abstract

A novel system for verifying signatures on Persian handwritten bank checks is presented, in this paper. The presented system includes two main phases called: training and verification phases. At first, the system is trained using some genuine signatures provided by each customer in training phase. Then verifying the signatures on incoming checks is carried out in the verification phase. Feature extraction step is conducted based on a new approach that uses Multitresolution box-counting (MRBC) method for estimating the fractal dimension of signatures. Here, signature verification is modeled as testing hypothesis, and decision about acceptance or rejection of signatures on incoming checks is carried out using Kolmogorov–Smirnov test. The presented system has been tested on two databases: our new created database and NISDCC database which was used for ICDAR 2009 signature verification competition. Our database has 1000 genuine signatures provided by 100 participants and 200 skilled forgeries copied from genuine samples by five forgers. In total our database includes 1200 Persian signatures. Obtained results show promising performance of the presented system for its application on Persian banks.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Explainable offline automatic signature verifier to support forensic handwriting examiners;Neural Computing and Applications;2023-11-20

2. Indoor Multi-Lingual Scene Text Database with Different Views;2023 International Symposium on Networks, Computers and Communications (ISNCC);2023-10-23

3. A Modified Deep Convolution Siamese Network for Writer-Independent Signature Verification;International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems;2022-06

4. Patch-based offline signature verification using one-class hierarchical deep learning;International Journal on Document Analysis and Recognition (IJDAR);2019-07-31

5. Nonlinear Dynamics Tools for Offline Signature Verification Using One-class Gaussian Process;International Journal of Pattern Recognition and Artificial Intelligence;2019-05-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3