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Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
Bangla OCR
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Bangla OCR

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Presentation on Bangla OCR

Presentation on Bangla OCR

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

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