Categorizing global and local features of on-line signature verification using DTW and fuzzy logic
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Karimi, R
Ghobadi, A
Amoli, PV
Mirjalili, S
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Abstract
In this paper, we study the online signature verification features to define their personalities and categorize them in different groups. We employed 30 features in four categories, a faster methodology using DTW and Fuzzy logic has been applied to find optimal solution based on the lowest Equal Error Rate (EER). At the end, we compare the result with the different methods proposed by other researchers.
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Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
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1
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© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Taherzadeh, G; Karimi, R; Ghobadi, A; Amoli, PV; Mirjalili, S, Categorizing global and local features of on-line signature verification using DTW and fuzzy logic, Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011, 2011, 1, pp. 349-353