Performance Comparison of Features on Devanagari Hand-printed Dataset

Devanagari script is being used in various languages, in south Asian subcontinent, such as Sanskrit, Rajasthani, Marathi and Nepali and it is also the script of Hindi, the mother tongue of majority of Indians. Recognition of handwritten characters of Devanagari alphabet set is an important area of research. The work done for the recognition of Devanagari handwritten script is negligible in literature despite it is being used by millions people in India and abroad and it has numerous applications. The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. There are many feature extraction methods available in literature. We have tested the recognition performance of about 5 feature extraction methods available in literature on Devanagari handwritten characters. A database of more than 25000 handwritten Devanagari characters is developed by collecting the samples from hundreds writers belonging to 43 Devanagari alphabets. The performance comparisons have been made using two classifiers MLP and SVM.