In handwritten character recognition, benchmark database plays an important
role in evaluating the performance of various algorithms and the results
obtained by various researchers. In Devnagari script, there is lack of such
official benchmark. This paper focuses on the generation of offline benchmark
database for Devnagari handwritten numerals and characters. The present work
generated 5137 and 20305 isolated samples for numeral and character database,
respectively, from 750 writers of all ages, sex, education, and profession. The
offline sample images are stored in TIFF image format as it occupies less
memory. Also, the data is presented in binary level so that memory requirement
is further reduced. It will facilitate research on handwriting recognition of
Devnagari script through free access to the researchers.Comment: 5 pages, 8 figures, journal pape
