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Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts

Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts. Olarik Surinta Mahasarakham University Thailand. Introduction. Palm leaf manuscripts have been a popular written media for over a thousand years in Southeast Asia

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Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts

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  1. Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts Olarik Surinta Mahasarakham University Thailand IIP2008

  2. Introduction • Palm leaf manuscripts have been a popular written media for over a thousand years in Southeast Asia • Palm leaves were used for recording the history, knowledge and local wisdoms such as • Medical treatments • Buddhist doctrine • The story of dynasties IIP2008

  3. Introduction (cont) • Mahasarakham University is establishing Palm Leaf Manuscript Preservation Project for the discovery, preservation and protection of palm leaf manuscripts from Northeast Thailand palm leaf manuscript IIP2008

  4. Proposed framework • We use palm leaf manuscripts consisting of 227 pages to do research work • The system processes consist of • Background elimination • Line segmentation, and • Character segmentation IIP2008

  5. Proposed framework (cont) Framework of the BILAN (palm leaf manuscripts) system IIP2008

  6. Convert Image from RGB color to Grey Image • We use this equation to convert RGB color to Grey image Y = 0.3R + 0.59G + 0.11B RGB color Grey image IIP2008

  7. Noise Reduction • Noise is maybe appearing from the scanning process. • This process is removing noise from Grey image using Gaussian Filtering grey image before and after noise reduction IIP2008

  8. Background Elimination using Otsu’s Algorithm • This method proposed by Otsu. It based on grey level histogram Otsu’s threshold value method IIP2008

  9. Background Elimination using Otsu’s Algorithm (cont) Grey image binary image after background elimination IIP2008

  10. Image recovery • We apply Mathematical Morphology in this research such as • Dilation • erosion binary image binary image after morphology IIP2008

  11. Line Segmentation • Projection profile analysis is a popular technique for line segmentation. • We use horizontal projection profile analysis because the texts in most document images are aligned along horizontal lines IIP2008

  12. Line Segmentation (cont) Line segmentation histogram Image after line segmentation IIP2008

  13. Line Segmentation (cont) IIP2008

  14. Character Segmentation • In this step, use vertical projection profile analysis. • we apply a threshold value on the length of the space in between the characters image after vertical projection profile IIP2008

  15. Experimental Results • The method was tested using a set of 227 palm leaf manuscripts IIP2008

  16. Background Elimination Results IIP2008

  17. Line Segmentation Results IIP2008

  18. Complete background elimination IIP2008

  19. Incomplete background elimination IIP2008

  20. Incomplete background elimination IIP2008

  21. Future work • Application this research for OCR system. • Translation Palm leaf manuscripts into Thai language. IIP2008

  22. End of this presentation Thank you very much IIP2008

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