OCR low-res image from specified set of characters

14 views (last 30 days)
Amit on 8 Feb 2016
Answered: Amit on 21 Feb 2016
Hello all:
Is there a way in which I provide the super set of characters (no characters to be expected outside the set) to the OCR. I mean to say for example if I know that my images has only [U, T, C, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, :, space] as the only characters, can I feed it to matlab OCR and thus expect better predictions.
Can this help somehow on low res image to increase the accuracy?
Kindly see the attached image I am struggling to get good results with.
Regards,
Amit

Image Analyst on 8 Feb 2016
For something like that you can probably just crop out each character and find the area. Then, assuming each character has a unique area, have a look up table where a certain area means the character must be a certain character.

Amit on 8 Feb 2016
Ingenious! So yo mean using functions like 'regionprops'?
Thanks @Image Analyst. Such an approach might be helpful for many other related things though I am just hoping for a simpler solution for this one particular case.
Please let me know if you have functions other than 'regionprops' in mind.
Regards,
Amit
Image Analyst on 10 Feb 2016
Right. Something like
measurements = regionprops(labeledImage, 'Area');
allAreas = [measurements.Area];
% Define character areas
characterAreas = [300,410,130,500,........] % Whatever they are.
for k = 1 : length(allAreas)
differences = abs(measurements(k).Area - characterAreas);
[~, closestCharacterIndex] = min(differences);
% Now you know what character it is....
end

Anand on 8 Feb 2016
Edited: Anand on 8 Feb 2016
This exact functionality is available in the ocr function. Use the 'CharacterSet' Name-Value pair to achieve this. Something like this:
ocrResults = ocr(yourImage,'CharacterSet','UTC1234567890')
In your case, you may have even more information that you can supply to the ocr function. If it's a valid assumption that the left half of the image only contains characters, you could have two calls to ocr with different ROI's.
For example (this is pseudo-code),
leftROI = [1 1 floor(size(im,2)/2) size(im,1)-1];
ocrLeftResults = ocr(im, leftROI, 'CharacterSet','UTC');
rightROI = [floor(size(im,2)/2)+1 1 floor(size(im,2)/2) size(im,1)-1];
ocrRightResults = ocr(im, rightROI, 'CharacterSet', '0123456789');

Amit on 8 Feb 2016
Great. And special characters ': #' etc. are not a problem? How about the french and German accented characters 'àâæçéèêëïîôœùûüÿ' etc.?
Thank you very much.
Anand on 8 Feb 2016
Amit, that should be perfectly fine. There is a list of supported languages which you can see here.
You need to add the Name-Value pair 'Language'.
Amit on 10 Feb 2016
Hello Anand, thank you. Its very helpful, though the low resolution of my image I guess is resulting in very bad quality of predictions.
Any thoughts.
Thanks again indeed.

Amit on 21 Feb 2016
Dear all:
Opening the question again. I have 2864 files such as one attached. I have not been able to find anything, MATLAB or otherwise that works reliably to give me the OCR out. That was my Sunday.