Handwritten Numeral Recognition using Composite Features and SVM classifier
نویسندگان
چکیده
منابع مشابه
Devnagari Handwritten Numeral Recognition using Geometric Features and Statistical Combination Classifier
This paper presents a Devnagari Numerical recognition method based on statistical discriminant functions. 17 geometric features based on pixel connectivity, lines, line directions, holes, image area, perimeter, eccentricity, solidity, orientation etc. are used for representing the numerals. Five discriminant functions viz. Linear, Quadratic, Diaglinear, Diagquadratic and Mahalanobis distance ar...
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Handwritten Devanagari Numeral Recognition using Structural and Statistical Features 1 Madhav Goyal, 2 Naresh Kumar Garg 1 Department of Computer Science & Engg, Guru Ram Dass Institute of Engg. & Technology, Bathinda, Punjab, India 2 Department of Computer Science & Engg, GZSPTU Campus, Bathinda, Punjab, India ____________________________________________________________________________________...
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We present a method of handwritten numeral recognition, where we introduce hierarchical Gabor features (HGFs) and construct a Bayesian network classifier that encodes the dependence between HGFs. We extract HGFs in such a way that they represent different levels of information which are structured such that the lower the level is, the more localized information they have. At each level, we choo...
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Recognition of Indian languages is a challenging problem. In Optical Character Recognition (OCR), acharacter or symbol to be recognized can be machine printed or handwritten characters/numerals. Several approaches in the past have been proposed that deal with problem of recognition of numerals/character depending on the type of feature extracted and way of extracting them. In this paper also a ...
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ژورنال
عنوان ژورنال: The Journal of the Korean Institute of Information and Communication Engineering
سال: 2010
ISSN: 2234-4772
DOI: 10.6109/jkiice.2010.14.12.2761