Converting Myanmar printed document image into machine understandable text format

Win, Htwe Pa Pa; Khine, Phyo Thu Thu; Tun, Khin Nwe Ni

doi:10.1109/icdim.2011.6093371

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…There are several binarization algorithms, but most existing works [8,13,27] have been using the Otsu [28] method. However, this method cannot give a satisfactory result when the input image had a shadow region or shadow background and lighting effects.…”

Section: Binarizationmentioning

confidence: 99%

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

Lwin

2019

IJSRST

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Optical Character Recognition (OCR) is a technology widely adopted for automatic translation of hardcopy text to editable text. The language dependence of the technology makes it far less developed for less popular languages like Myanmar language. Also, the uniqueness and complexity of the Myanmar text system such as touching and complex characters have continued to pose serious challenges to several OCR investigators. In this paper, we propose a new technique to development Myanmar OCR system. Our technique implement skew angle detection and free skew, noisy border correction, extra page elimination, line segmentation from scanned images of Myanmar text. Performance of the proposed method is tested with 430 documents comprising different printed and handwritten Myanmar text of various fonts, sizes, multi-column, tables, stamps or photos, background effects. Our method give an accuracy of 100% for line segmentation and 99.92% for skew angle detection and free skew. The ability of our method to effectively implement global and local skew angle detection, free skew and line segmentation in different handwritten and digital text images of the Myanmar character set with high accuracies confirms the robustness of the technique, its reliability and its suitability for application in many other related languages.

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Section: Binarizationmentioning

confidence: 99%

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

Lwin

2019

IJSRST

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“…Finally, the binarized image is deskewed with generalized Hough Transformed method. The detailed of the preprocessing steps are described in Win and Tun (2010).…”

Section: Preprocessingmentioning

confidence: 99%

Character Segmentation Scheme for OCR System

Win

Khine

Tun

2011

International Journal of Computer Vision and Image Processing

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Automatic machine-printed Optical Characters or texts Recognizers (OCR) are highly desirable for a multitude of modern IT applications, including Digital Library software. However, the state of the art OCR systems cannot do for Myanmar scripts as the language poses many challenges for document understanding. 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. 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. 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. The proposed algorithms have been tested on a variety of Myanmar printed documents and the results of the experiments indicate that the methods can increase the segmentation accuracy as well as recognition rates.

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Myanmar Handwritten Character Recognition from Similar Character Groups Using K-Means and Convolutional Neural Network

Lwin

2020

2020 IEEE 3rd International Conference on Electronics and Communication Engineering (ICECE)

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Converting Myanmar printed document image into machine understandable text format

Cited by 6 publications

References 12 publications

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

Image Purification Technique for Myanmar OCR Applying Skew Angle Detection and Free Skew

Character Segmentation Scheme for OCR System

Myanmar Handwritten Character Recognition from Similar Character Groups Using K-Means and Convolutional Neural Network

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