Table 11 Statistical analysis of various offline signature datasets.
From: A hybrid machine learning framework for offline signature verification using gray wolf optimization
Dataset | No. of Images | \(\:{\varvec{S}}_{\varvec{i}\varvec{n}\varvec{t}\varvec{r}\varvec{a}}\) | \(\:{\varvec{D}}_{\varvec{i}\varvec{n}\varvec{t}\varvec{e}\varvec{r}}\) | \(\:\varvec{D}\varvec{I}\) | \(\:{\varvec{C}}_{\varvec{s}\varvec{c}\varvec{o}\varvec{r}\varvec{e}}\) | Accuracy (%) |
|---|---|---|---|---|---|---|
CEDAR | 2,640 | 0.72 | 12.3 | 2.85 | 0.78 | 99.4 |
SID | 5,626 | 0.67 | 14.1 | 2.34 | 0.71 | 97.22 |
BHSig260 | 13,000+ | 0.70 | 13.5 | 2.63 | 0.76 | 98.8 |
DeepSignVault | 1,000 | 0.69 | 13.8 | 2.52 | 0.74 | 96.96 |
