![]() ![]() To reveal the effectiveness of the segmentation technique, the authors follow a new hybrid feature extraction method and choose the SVM classifier for recognition of the character image. ![]() ![]() In order to get more accurate system, the authors propose the method for isolation of the character image by using not only the projection methods but also structural analysis for wrongly segmented characters. Therefore, the authors design an Optical Character Recognition System for Myanmar Printed Document (OCRMPD), with several proposed techniques that can automatically recognize Myanmar printed text from document images. However, the state of the art OCR systems cannot do for Myanmar scripts as the language poses many challenges for document understanding. AbstractAutomatic machine-printed Optical Characters or texts Recognizers (OCR) are highly desirable for a multitude of modern IT applications, including Digital Library software.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |