  In this paper a scheme for offline Handwritten Devnagari Character
Recognition is proposed, which uses different feature extraction methodologies
and recognition algorithms. The proposed system assumes no constraints in
writing style or size. First the character is preprocessed and features namely
: Chain code histogram and moment invariant features are extracted and fed to
Multilayer Perceptrons as a preliminary recognition step. Finally the results
of both MLP's are combined using weighted majority scheme. The proposed system
is tested on 1500 handwritten devnagari character database collected from
different people. It is observed that the proposed system achieves recognition
rates 98.03% for top 5 results and 89.46% for top 1 result.
