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2010 | 19 |

Article title

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

Content

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Languages of publication

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.

Publisher

Year

Volume

19

Physical description

Dates

published
2010
online
08 - 07 - 2015

Contributors

References

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.ojs-issn-2083-8476-year-2010-volume-19-article-3000
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