DocumentCode :
2726622
Title :
On-line Signature Verification: An Approach Based on Cluster Representations of Global Features
Author :
Guru, D.S. ; Prakash, H.N. ; Manjunath, S.
Author_Institution :
Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore
fYear :
2009
fDate :
4-6 Feb. 2009
Firstpage :
209
Lastpage :
212
Abstract :
In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global features of signatures of each cluster are used to form an interval valued feature vector which is a symbolic representation for a cluster. Based on cluster representation, we propose methods of signature verification. We compare the feasibility of the proposed representation scheme for signature verification on a large MCYT_ signature database of 16500 signatures. Unlike other signature verification methods, the proposed method is simple and efficient and in addition, shows a remarkable reduction in EER.
Keywords :
handwriting recognition; image representation; image segmentation; pattern clustering; vectors; feature dependent threshold; global feature clustering; interval valued feature vector; online signature representation; online signature verification; symbolic representation; Computer science; Data analysis; Fuzzy neural networks; Handwriting recognition; Hidden Markov models; Neural networks; Pattern recognition; Shape; Spatial databases; Support vector machines; Fuzzy C-means (FCM) clustering; Global features; On-line signature verification; Symbolic feature vector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Pattern Recognition, 2009. ICAPR '09. Seventh International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-3335-3
Type :
conf
DOI :
10.1109/ICAPR.2009.30
Filename :
4782776
Link To Document :
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