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Unconstrained handwritten character recognition based on fuzzy logic |
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| Authors: | M HanmandluAuthor Vitae Sourav ChakrabortyAuthor Vitae |
| Affiliation: | a Faculty of Engineering (FOE), Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selongor, Malaysia b Supercomputer Division, NCMRWF, Department of Science and Technology, Mausam Bhavan Complex, Lodi Road, New Delhi 110 003, India c Department of Computer Science, University of Delhi, Delhi, India d Department of Electronics and Communication Engineering, S.N.S. College of Engineering, Mohali, Punjab, India e Department of Computer Engineering, Delhi College of Engineering, Delhi, India |
| Abstract: | This paper presents an innovative approach called box method for feature extraction for the recognition of handwritten characters. In this method, the binary image of the character is partitioned into a fixed number of subimages called boxes. The features consist of vector distance (γ) from each box to a fixed point. To find γ the vector distances of all the pixels, lying in a particular box, from the fixed point are calculated and added up and normalized by the number of pixels within that box. Here, both neural networks and fuzzy logic techniques are used for recognition and recognition rates are found to be around 97 percent using neural networks and 98 percent using fuzzy logic. The methods are independent of font, size and with minor changes in preprocessing, it can be adopted for any language. |
| Keywords: | Box method Handwritten characters Neural networks and fuzzy logic |
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