CEDAR Signature is a database of off-line signatures for signature verification. Each of 55 individuals contributed 24 signatures thereby creating 1,320 genuine signatures. Some were asked to forge three other writers’ signatures, eight times per subject, thus creating 1,320 forgeries. Each signature was scanned at 300 dpi gray-scale and binarized using a gray-scale histogram. Salt pepper noise removal and slant normalization were two steps involved in image preprocessing. The database has 24 genuines and 24 forgeries available for each writer.
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The AND Dataset contains 13700 handwritten samples and 15 corresponding expert examined features for each sample. The dataset is released for public use and the methods can be extended to provide explanations on other verification tasks like face verification and bio-medical comparison. This dataset can serve as the basis and benchmark for future research in explanation based handwriting verification.
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The BRUSH dataset (BRown University Stylus Handwriting) contains 27,649 online handwriting samples from a total of 170 writers. Every sequence is labeled with intended characters such that dataset users can identify to which character a point in a sequence corresponds. The dataset was introduced in the paper "Generating Handwriting via Decoupled Style Descriptors" by Atsunobu Kotani, Stefanie Tellex, James Tompkin from Brown University, presented at European Conference on Computer Vision (ECCV) 2020.
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A dataset with $23\,870$ digital trajectories (i.e. time series) of handwritten lower- and uppercase Latin letters and Arabic numbers ($a$-$z$, $A$-$Z$, $0$-$9$), generated by $77$ experts using a Wacom Pen Tablet. An expert is considered a proficient user of the recorded symbols, in this case adult native German speakers.
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