ICTACT Journal on Image and Video Processing

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Application of SVM and Soft Features to Azerbaijani Text Recognition


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1 Department of General and Applied Mathematics, Azerbaijan State Oil and Industry University, Azerbaijan
     

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The purpose of this study is to establish more accurate and less time-consuming recognition system for Azerbaijani text recognition. The main problem of investigating and developing recognition systems is the extraction of features, in view of the fact that, most of current recognition systems use features, which are unintelligible for human mind and proposed for operating by computers. For eliminating above-mentioned problem, in this paper was offered “soft” features, extracted on base of human-mind techniques. On the side of validating SVM approach and “soft” features provided in this paper, experiments were executed using various feature classes offered for Azerbaijani hand-printed characters and different methods.

Keywords

SVM, Soft Features, Hand-Printed Characters, Characters Recognition, Features Extraction.
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  • Application of SVM and Soft Features to Azerbaijani Text Recognition

Abstract Views: 226  |  PDF Views: 1

Authors

Elviz A. Ismayilov
Department of General and Applied Mathematics, Azerbaijan State Oil and Industry University, Azerbaijan

Abstract


The purpose of this study is to establish more accurate and less time-consuming recognition system for Azerbaijani text recognition. The main problem of investigating and developing recognition systems is the extraction of features, in view of the fact that, most of current recognition systems use features, which are unintelligible for human mind and proposed for operating by computers. For eliminating above-mentioned problem, in this paper was offered “soft” features, extracted on base of human-mind techniques. On the side of validating SVM approach and “soft” features provided in this paper, experiments were executed using various feature classes offered for Azerbaijani hand-printed characters and different methods.

Keywords


SVM, Soft Features, Hand-Printed Characters, Characters Recognition, Features Extraction.

References