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- W2098340238 abstract "Evaluates the extended shadow code used as a global feature vector for the signature verification problem. The latter as a shape factor is very easy to implement. Numerical experiments have been made with a signature database of 800 images (20 writers /spl times/ 40 signatures per writer) in the context of random forgeries. In the first experiment, a kNN classifier with voting shows a mean total error rate of 0.01% with k=1. In the second experiment, a minimum distance classifier has been used. The thresholds were evaluated for each of the 20 writers, and the number of reference signatures was varied in the range 1 /spl les/ N/sub ref/ /spl les/ 10. The mean total error rate was below 1.00% with N/sub ref/ = 4 genuine signatures. >" @default.
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- W2098340238 date "2002-12-30" @default.
- W2098340238 modified "2023-09-26" @default.
- W2098340238 title "An extended-shadow-code based approach for off-line signature verification" @default.
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- W2098340238 doi "https://doi.org/10.1109/icdar.1993.395795" @default.
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