Recognition of Devanagari Handwritten Numerals using Gradient Features and SVM
Ashutosh Aggarwal, Rajneesh Rani, Renu Dhir · International Journal of Computer Applications · 2012
Recognition of Indian languages is a challenging problem.In Optical Character Recognition (OCR), acharacter or symbol to be recognized can be machine printed or handwritten characters/numerals.Several approaches in the past have been proposed that deal with problem of recognition of numerals/character depending on the type of feature extracted and way of extracting them.In this paper also a recognition system for isolated Handwritten Devanagari Numerals has been proposed.The proposed system is based on the division of sample image into sub-blocks and then in each sub-block Strength of Gradient is accumulated in 8 standard directions in which Gradient Direction is decomposed resulting in a feature vector with dimensionality of 200.Support Vector Machine (SVM) is used for classification.Accuracy of 99.60% has been obtained by using standard dataset provided by ISI (Indian Statistical Institute) Kolkata.