Title :
Multistage Recognition Approach for Handwritten Devanagari Script Recognition
Author :
Rahul, P.V. ; Gaikwad, Arun N.
Author_Institution :
Dept. of Electron. Eng., Bharati Vidyapeeth, Pune, India
fDate :
Oct. 30 2012-Nov. 2 2012
Abstract :
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.
Keywords :
feature extraction; handwritten character recognition; image segmentation; learning (artificial intelligence); natural language processing; self-organising feature maps; vector quantisation; alphabet set; artificial neural network; feature extraction; feature vector; handwritten Devanagari script recognition; image preprocessing; image segmentation; learning vector quantization; multistage recognition approach; network training; numeral set; self-organizing map; word image scanning; Educational institutions; Feature extraction; Handwriting recognition; Image segmentation; Organizing; Training; Vectors; Feature Extraction; Image Preprocessing; Network Neighborhood; Segmentation; Self Organizing Map;
Conference_Titel :
Information and Communication Technologies (WICT), 2012 World Congress on
Conference_Location :
Trivandrum
Print_ISBN :
978-1-4673-4806-5
DOI :
10.1109/WICT.2012.6409156
