DocumentCode
671781
Title
Off-line Bangla signature verification: An empirical study
Author
Pal, Shovon ; Alaei, Alireza ; Pal, Umapada ; Blumenstein, Michael
Author_Institution
Dept. of Sch. of Inf. & Commun. Technol., Griffith Univ., Brisbane, QLD, Australia
fYear
2013
fDate
4-9 Aug. 2013
Firstpage
1
Lastpage
7
Abstract
Among all of the biometric authentication systems, handwritten signatures are considered as the most legally and socially accepted attributes for personal verification. The objective of this paper is to present an empirical contribution towards the understanding of a threshold-based signature verification technique involving off-line Bangla (Bengali) signatures. Experiments on signature verification involving non-English signatures are an important consideration in the signature verification area. Only very few research works employing signatures of Indian script have been considered in the field of non-English signature verification. To fill this gap, a threshold-based scheme for verification considering off-line Bangla signatures is proposed. Some techniques such as under-sampled bitmap, intersection/endpoint and directional chain code are employed for feature extraction. The Nearest Neighbour method is considered for classification. Furthermore, a Bangla signature database, which consists of 2400 (100×24) genuine signatures and 3000 (100×30) forgeries has been created and is employed for experimentation. We obtained a 15.57% Average Error Rate (AER) as the best verification result using directional chain code features employed in this research work.
Keywords
biometrics (access control); feature extraction; handwriting recognition; natural language processing; visual databases; AER; Bangla signature database; average error rate; biometric authentication systems; directional chain code; directional chain code features; empirical study; feature extraction; handwritten signatures; nonEnglish signatures; offline Bangla signature verification; personal verification; signature verification technique; Authentication; Databases; Error analysis; Feature extraction; Forgery; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location
Dallas, TX
ISSN
2161-4393
Print_ISBN
978-1-4673-6128-6
Type
conf
DOI
10.1109/IJCNN.2013.6707123
Filename
6707123
Link To Document