Conference or Workshop Item #18152

(2020) Offline Handwritten Signature Verification Based on Circlet Transform and Statistical Features. In: 1st International Conference on Machine Vision and Image Processing, MVIP 2020, 19 February 2020through 20 February 2020, Tehran, Iran.

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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. © 2020 IEEE.

Item Type: Conference or Workshop Item (Paper)
Keywords: Circlet Transform Gray Level Co-occurrence Matrix Index Terms - Offline Handwritten Signature Verification Statistical Feature Cost effectiveness Authentication systems Benchmark datasets Financial applications Financial transactions Off-line handwritten signature verification Signature verification methods Statistical features Statistical properties Computer vision
Subjects: W General Medicine. Health Professions > W 322-323 Social Welfare through Medicine
W General Medicine. Health Professions > W 87-96 Professional Practice
Divisions: School of Advanced Technologies in Medicine > Department of Bioelectrics and Biomedical Engineering
Journal Index: Scopus
Volume: 2020-F
Publisher: IEEE Computer Society
Identification Number: https://doi.org/10.1109/MVIP49855.2020.9116909
ISBN: 21666776 (ISSN); 9781728168326 (ISBN)
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/18152

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