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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["http://i.stack.imgur.com/keYUf.png"],"Byte"]]]]

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

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

Could anyone can give some advice?

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  • $\begingroup$ 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 '17 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 '17 at 18:07

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