ER2: An Intuitive Similarity Measure for On-Line Signature Verification

Authors:
Hansheng Lei;Srinivas Palla;Venu Govindaraju
Affiliations:
State University of New York at Buffalo;State University of New York at Buffalo;State University of New York at Buffalo
Venue:
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Year:
2004

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Abstract

ER虏 (Extended R-squared) is proposed as a similarity measure for on-line signature verification. SLR (Simple Linear Regression) defines R虏 as a measure of goodness-of-fit. We observed that R虏 is a good similarity measure for 1-dimensional sequences. However, many kinds of sequences are multidimensional, such as on-line signature sequences, 2D curves, etc. Therefore, we extend R虏 to ER虏 for multidimensional sequence matching. Coupled with optimal alignment, ER虏 outperforms DTW-based curve matching on on-line signature verification.