Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45488
Title: Robust score normalization for DTW-based on-line signature verification
Authors: Fischer, Andreas
Diaz, Moises 
Plamondon, Rejean
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Hidden Markov models
Cognition
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Issue Date: 2015
Journal: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
Conference: 13th IAPR International Conference on Document Analysis and Recognition (ICDAR) 
13th International Conference on Document Analysis and Recognition, ICDAR 2015 
Abstract: In the field of automatic signature verification, a major challenge for statistical analysis and pattern recognition is the small number of reference signatures per user. Score normalization, in particular, is challenged by the lack of information about intra-user variability. In this paper, we analyze several approaches to score normalization for dynamic time warping and propose a new two-stage normalization which detects simple forgeries in a first stage and copes with more skilled forgeries in a second stage. An experimental evaluation is conducted on two data sets with different characteristics, namely the MCYT online signature corpus, which contains over three hundred users, and the SUSIG visual sub-corpus, which contains highly skilled forgeries. The results demonstrate that score normalization is a key component for signature verification and that the proposed two-stage normalization achieves some of the best results on these difficult data sets both for random and for skilled forgeries.
URI: http://hdl.handle.net/10553/45488
ISBN: 9781479918058
ISSN: 1520-5363
DOI: 10.1109/ICDAR.2015.7333760
Source: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR[ISSN 1520-5363],v. 2015-November (7333760), p. 241-245
Appears in Collections:Actas de congresos
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