Multistage Recognition Approach for Handwritten Devanagari Script Recognition

This paper is focused on Devanagari Handwritten Script Recognition. The scanned word image is taken as an input image. An Input image is preprocessed and segmented. The features are extracted. Feature vector is applied to an artificial Neural Network. The Network is trained for the different set of numerals and alphabets. Output of Self Organizing Map applied to Learning Vector Quantization and the accuracy is calculated.