Conversion and Recognition of Handwritten Devnagari Character String into Printed Character String Using KNN

This paper presents a system for the conversion of handwritten string of Devnagari character to printed character string by using character segmentation approach. 11 different statistical features of segmented characters are extracted which are compared with features extracted from printed string of characters available in training data for cross validation purpose using Knearest neighborhood (kNN) algorithm. Use of handwritten string of Devnagari characters written in different styles and converting it into printed string makes the system more prone to real life application. System mainly works on segmentation of characters using bounding box, after segmentation, features are extracted which is compared with training feature set. We have analyzed our system with existing Devnagari handwritten character recognition systems. In given framework, we have focused on a creating database in different styles and recognizing them as printed characters. Keywords— K-Nearest Neighborhood Algorithm, Connected Components Labeling, Bounding Box, Statistical Feature, Feature Extraction Technique, Handwritten Devnagari string segmentation, Object extraction, Printed String of Characters.

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