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 :
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