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To show the effectiveness of the proposed method, this paper assumed the documents are successfully segmented into characters and extracted features from these isolated Myanmar characters. These features are extracted using structural analysis of the Myanmar scripts. The experimental results have been carried out using the Support Vector Machine (SVM) classifier and compare the pervious proposed feature extraction method.<\/p>","DOI":"10.4018\/ijcvip.2012010102","type":"journal-article","created":{"date-parts":[[2012,12,11]],"date-time":"2012-12-11T14:18:23Z","timestamp":1355235503000},"page":"16-41","source":"Crossref","is-referenced-by-count":1,"title":["A Structural Analysis Based Feature Extraction Method for OCR System For Myanmar Printed Document Images"],"prefix":"10.4018","volume":"2","author":[{"given":"Htwe Pa Pa","family":"Win","sequence":"first","affiliation":[{"name":"University of Computer Studies-Yangon, Myanmar"}]},{"given":"Phyo Thu Thu","family":"Khine","sequence":"additional","affiliation":[{"name":"University of Computer Studies-Yangon, Myanmar"}]},{"given":"Khin Nwe Ni","family":"Tun","sequence":"additional","affiliation":[{"name":"University of Computer Studies-Yangon, Myanmar"}]}],"member":"2432","reference":[{"key":"ijcvip.2012010102-0","doi-asserted-by":"crossref","unstructured":"Agrawal, M., & Doermann, D. 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