1
$\begingroup$

I have a big complaint about function TextRecognize. Alexey Popkov have verified here. Actually it can do it as the attribute "BoundingBox" if the function is normally.

HighlightImage[ColorNegate[Binarize[img1]], 
 TextRecognize[img1, "Word", "BoundingBox"]]

But as you see,it will give a very bad result.Since the MMA have the function of neural-networks,so I want to expect a neural-networks method to find all number and the position of the number. I have some samples image here for test

img1=Uncompress[FromCharacterCode[
  Flatten[ImageData[Import["https://i.stack.imgur.com/keYUf.png"],"Byte"]]]]

img2 = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["https://i.stack.imgur.com/U86l9.png"],"Byte"]]]]

img3=Uncompress[FromCharacterCode[
  Flatten[ImageData[Import["https://i.stack.imgur.com/V76u5.png"],"Byte"]]]]

Could anyone can give some advice?

Improve this question
$\endgroup$
2
  • $\begingroup$ I think a traditional method may be easier. For example, use something like ContourDetect[img1] to detect the position of the numbers and characters, and then crop out the numbers and characters and feed them into a classifier. $\endgroup$
    – xslittlegrass
    Sep 22, 2017 at 17:33
  • $\begingroup$ @xslittlegrass Sorry, the processed image alway is gray image. and I cannot ensure the line of the frame will be more black than the digtal.So I have edited that original image just now.. $\endgroup$
    – yode
    Sep 22, 2017 at 18:07

0

Reset to default

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Browse other questions tagged or ask your own question.