BibTeX:

@article{IJIRSTV1I11080,
     title={Offline Recognition of Handwritten Devanagari words using Hidden Markov Model},
     author={Mrs. Asma Shaikh and Mr. Rahul Dagade,},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={11},
     pages={526--531},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I11080.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Devanagari is the most popular script in India use by more than 500 million people. The handwriting recognition area has been researched extensively till date, whereas offline recognition of Devanagari script is progressing area of research. This system involves three steps, pre-processing, feature extraction and classification respectively. In the first stage words from input images are normalized. Then, a set of intensity features are extracted from each of the segmented words. Gradient features are extracted from an image Then structure-like features are also extracted. Finally, these features are applied in a combined scheme for classification. Intensity features & Gradient features are used to train a HMM classifier, whose results are re-ranked using structural features for improved recognition rate.

HWR, HMM, Classifier, Re-ranking etc