Author(s): Gunvantsinh Gohil | Rekha Teraiya | Mahesh Goyani
Journal: International Journal of Artificial Intelligence & Applications
ISSN 0976-2191
Volume: 3;
Issue: 1;
Start page: 95;
Date: 2012;
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Keywords: Pre-processing | Segmentation | Histogram | Neural Network | Support Vector Machine
ABSTRACT
Optical Character Recognition Systems are getting more and more attention in recent decade. In manycountries, OCR has been a part of their government sectors like post offices, Library automation, LicensePlate Recognition, Defence organization etc. According to recent survey, there are at least 550 millionpeople are using Devanagari script for communication. Hindi is one of the language, which is derived fromDevanagari script. For any character recognition system, essential step is to identify individual characterand find features to compare it with the template features. In this paper, we have proposed histogram basedhierarchical approach for isolating individual character from the image document. We have used PrincipleComponent Analysis and Fisher Discriminant Analysis kind of holistic features for recognition. We havedone the comparisons of such holistic features with geometric features like binary features and chain code.
Journal: International Journal of Artificial Intelligence & Applications
ISSN 0976-2191
Volume: 3;
Issue: 1;
Start page: 95;
Date: 2012;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Pre-processing | Segmentation | Histogram | Neural Network | Support Vector Machine
ABSTRACT
Optical Character Recognition Systems are getting more and more attention in recent decade. In manycountries, OCR has been a part of their government sectors like post offices, Library automation, LicensePlate Recognition, Defence organization etc. According to recent survey, there are at least 550 millionpeople are using Devanagari script for communication. Hindi is one of the language, which is derived fromDevanagari script. For any character recognition system, essential step is to identify individual characterand find features to compare it with the template features. In this paper, we have proposed histogram basedhierarchical approach for isolating individual character from the image document. We have used PrincipleComponent Analysis and Fisher Discriminant Analysis kind of holistic features for recognition. We havedone the comparisons of such holistic features with geometric features like binary features and chain code.
