Help on character segmentation for license plate recognition

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Hi all,
currently I am working on a code for license plate recognition, I have finished coding for license plate extraction,I need help for character segmentation into individual character for some of the connected character inside the car plate.I'm thinking to use FFT2 to improve the edge of the image and then inverse it back using IFFT..is that possible to do this??
output image:
Second image after thresholding

Accepted Answer

Sean de Wolski
Sean de Wolski on 2 Jun 2011
You know how wide a character is, I would begin with that knowledge to indiscriminately segment the characters from each other.
  1. start at left edge, set all values in the column x_length over to black, repeat until edge of that connected component.
  2. repeat with next CC etc.
  4 Comments
Catherine
Catherine on 4 Jun 2011
not always,my database have six or seven characters inside the image.The majority is 7 characters.Yes there are always at small angle.
http://i1202.photobucket.com/albums/bb375/ShuWei88/w2-1.jpg
Here is the image after some thresholding process when i cropped my detected car plate region and filtering of small particles..skeletonization??what function does it involve??this is the image after skeletonization...thanks =)
http://i1202.photobucket.com/albums/bb375/ShuWei88/untitled.jpg
Catherine
Catherine on 18 Jun 2011
Hi sean de!i have solve the segmentation problem for the connected characters by using width and height ratio and its work.Did u know how to combine the different output image which are same size into a single image??i got 6 sub image and i wish to combine them into 1,hope u can help...
thanks

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More Answers (1)

Image Analyst
Image Analyst on 4 Jun 2011
No, I don't think that edge enhancement should be necessary. Why do you think it should? I think you need to study on on OCR algorithms first to see how the pros do it: http://iris.usc.edu/Vision-Notes/bibliography/contentschar.html#OCR,%20Document%20Analysis%20and%20Character%20Recognition%20Systems

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