Development of Comprehensive Devnagari Numeral and Character Database for Offline Handwritten Character Recognition
This provides a free, accessible benchmark for researchers working on offline handwritten character recognition in Devnagari script, addressing a domain-specific gap.
The paper tackled the lack of an official benchmark database for Devnagari script by generating a comprehensive offline database of handwritten numerals and characters, resulting in 5,137 numeral samples and 20,305 character samples collected from 750 diverse writers.
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.