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Gujarati Character Recognition using Zoning Density and K-NN Algorithm


Modi Gaurav S , saffrony institute; Chauhan Nandish, saffrony institute


OCR, Segmentation, Zoning Density, Euclidean Distance, K-NN Classifier


In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper we propose Zone based features for recognition of the Printed Gujarati Characters. A digital image is divided into 64 zones and pixel density is computed for each zone. This procedure is sequentially repeated for entire zone. Finally 64 features are extracted for classification and recognition. There could be some zone column/row having empty foreground pixels. Hence the feature value of such particular zone column/row in the feature vector is zero. The KNN classifier is used to classify the printed Gujarati Characters.

Other Details

Paper ID: IJSRDV3I31194
Published in: Volume : 3, Issue : 3
Publication Date: 01/06/2015
Page(s): 1951-1954

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