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2010 | 19 |
Article title

Investigation of Normalization Techniques and Their Impact on a Recognition Rate in Handwritten Numeral Recognition

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PL
Abstracts
PL
This paper presents several normalization techniques used in handwritten numeral recognition and their impact on recognition rates. Experiments with five different feature vectors based on geometric invariants, Zernike moments and gradient features are conducted. The recognition rates obtained using combination of these methods with gradient features and the SVM-rbf classifier are comparable to the best state-of-art techniques.
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Year
Volume
19
Physical description
Dates
published
2010
online
08 - 07 - 2015
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YADDA identifier
bwmeta1.element.ojs-issn-2083-8476-year-2010-volume-19-article-3000
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