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Bangla OCR

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Presentation on Bangla OCR

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Bangla OCR

  1. 1. Presented By Md. Al Imran Department of Computer Science & Engineering Khulna University of Engineering & Technology 12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  2. 2. <ul><li>Introduction </li></ul><ul><li>Applications </li></ul><ul><li>Related Works </li></ul><ul><li>Process Sequence </li></ul><ul><li>Outer Shape Detection Technique(OSDT) </li></ul><ul><li>Shape of Some Characters using OSDT </li></ul><ul><li>Performance Analysis </li></ul><ul><li>Comparisons </li></ul><ul><li>Conclusion </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  3. 3. <ul><li>OCR means Optical Character Recognition. </li></ul><ul><li>Bangla OCR System converts printed Bangla text into electronic version. </li></ul><ul><li>It is one of the challenging fields in recognition of printed Bangla text. </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  4. 4. <ul><li>Bangla OCR has many applications like </li></ul><ul><li>reading aid for the blind (OCR and speech synthesis), </li></ul><ul><li>automatic text entry into the computer(such as ledgering, sorting of postal mail, bank cheques etc) </li></ul><ul><li>desktop publication, </li></ul><ul><li>library cataloging etc. </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  5. 5. <ul><li>There exists some Bangla OCR Techniques which use Neural Network, super imposed matrices etc. </li></ul><ul><li>Needs training of each character. e.g. </li></ul><ul><li>We introduced a new technique, OSDT. </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  6. 6. <ul><li>Here is the block diagram of whole process </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  7. 7. <ul><li>Image Acquisition & Image Filtering </li></ul><ul><ul><li>We took an image as input </li></ul></ul><ul><ul><li>Applied Filtering </li></ul></ul><ul><li>Gray Scale Conversion & Binary Conversion </li></ul><ul><ul><li>Inputted image was converted as 1,0 format like matrix </li></ul></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  8. 8. <ul><li>Segmentation of Text image </li></ul><ul><ul><li>To do this, we used the following steps </li></ul></ul><ul><ul><ul><li>Line Segmentation </li></ul></ul></ul><ul><ul><ul><li>Word Segmentation and </li></ul></ul></ul><ul><ul><ul><li>Character Segmentation </li></ul></ul></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  9. 9. <ul><li>Matrix as 2-D array was used </li></ul><ul><li>Pixel was scanned horizontally </li></ul><ul><li>Starting binary data & ending binary data was stored for further processing(e.g. 1) </li></ul><ul><li>Distortion of word </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Figure 2: Segmentation of line from text
  10. 10. <ul><li>Matrix as 2-D array was used </li></ul><ul><li>Pixel was scanned vertically </li></ul><ul><li>Separation between words was detected when certain numbers of (vary with dimension of font) vertical lines containing all white pixels </li></ul><ul><li>Location of words was stored for further processing </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Inter Word gape Figure 3: Segmentation of word from line
  11. 11. <ul><li>Remove ‘ matra ’ from word </li></ul><ul><li>Pixel was scanned vertically </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Full ‘ matra ’ Inter Word Gap Figure 4: Classification of words considering ‘ matra ’
  12. 12. <ul><li>Left Scanning </li></ul><ul><li>Right Scanning </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 (a) (b) Figure 5: (a) Binary representation of a character (b) Inner and Outer Shape of a character
  13. 13. <ul><li>L means Left turn </li></ul><ul><li>R means right turn </li></ul><ul><li>V means vertical </li></ul><ul><li>S means straight </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  14. 14. 12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Table 3: Summary of simulation results
  15. 15. 12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Figure 6: Total execution time (second) over different number of characters inputted Figure 7: Accuracy of techniques over different font size
  16. 16. 12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009 Figure 8: Error rate (%) observed over different number of characters inputted
  17. 17. <ul><li>Different font size </li></ul><ul><li>Different number of characters </li></ul><ul><li>Future work </li></ul><ul><li>Scanned image </li></ul><ul><li>Background image </li></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  18. 18. <ul><li>http://code.google.com/p/banglaocr/downloads/detail?name=BanglaOCR%20V%200.6%20Setup%20%28for%20windows%29.zip&can=2&q = </li></ul><ul><ul><li>http://www.apona-bd.com/bangla-ocr/bangla-ocr-apona-pathak-2.html </li></ul></ul>12th International Conference on Computer and Information Technology (ICCIT 2009) December 24, 2009
  19. 19. December 24, 2009 12th International Conference on Computer and Information Technology (ICCIT 2009)

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