Abstract

Bangla handwritten character recognition is one of the complex works because of the wide variation of the Bangla character. In this paper we proposed a new approach for extracting the features of Bangla handwritten characters and then recognition of those characters using artificial neural network has done. For the feature extraction process we have used a row and column basis segmentation process in which a binary image the ratio of the dispersion of black from the top of the segment and total number of column or row pixels is measured on that particular segment as well as for each segment and then from this data a feature matrix of M×1 dimension is created for each character. When features from all the characters are extracted then some of the data is used to train the feed forward neural network and after that some characters are used for testing. In our proposed method 94.3% recognition accuracy is obtained when tested on some handwritten Bangla characters.

Keywords:
Bengali Pattern recognition (psychology) Artificial intelligence Computer science Character (mathematics) Artificial neural network Feature extraction Feature (linguistics) Intelligent word recognition Dimension (graph theory) Character recognition Pixel Segmentation Binary image Column (typography) Image (mathematics) Intelligent character recognition Image processing Mathematics Frame (networking)

Metrics

5
Cited By
0.24
FWCI (Field Weighted Citation Impact)
13
Refs
0.59
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Image Processing and 3D Reconstruction
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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