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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MatriVasha the largest dataset of handwritten Bangla compound characters for research on handwritten Bangla compound character recognition. The proposed dataset contains 120 different types of compound characters that consist of 306,464 images written where 152,950 male and 153,514 female handwritten Bangla compound characters. This dataset can be used for other issues such as gender, age, district base handwriting research because the sample was collected that included district authenticity, age group, and an equal number of men and women.
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