Drawing in the images

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Sepp
Sepp on 30 Apr 2014
Edited: Sepp on 1 Jun 2014
Hi
I want to develop a procedure to remove some inpainted text from images, i.e. I have to estimate the inpainted pixels. I will do that with first an imputation step and then applying SVD (and perhaps later further improvements).
The imputations step just have to give an initial guess of the inpainted pixels. I thought of applying a gaussian filter to get estimates of the inpainted pixels, but I think this does not give good results.
Does somebody know another way to get good inital guesses, i.e. imputations?

Accepted Answer

Image Analyst
Image Analyst on 30 Apr 2014
I don't know how "imputation" applies to an image. What algorithm is that?
If the text was inpainted, and the inpainting was good, it will smear the surrounding through the text and it will basically disappear. It can be detected however - you can't get back the original text, but you can tell where the inpainting occurred. There are some forensic methods to detect such alterations in an image. And there are methods people use to try to prevent that - those methods are called anti-forensics. And there are even, believe it or not, forensic methods that try to detect when anti-forensic processed have been employed. These are called "counter anti-forensics". You might think I'm joking, but I'm not. Earlier this year I attended a few papers from a conference on it at a larger symposium.
I don't know how you'd use SVD. Why do you think you can? Have you seen a paper on that? Otherwise do a web search for "image forensics". The think is, I don't know how you can remove the inpainting. Once you detect where it was applied, what do you mean by "remove" it? Do you mean replace with black pixels, to make a guesstimate at what the original text might have looked like? That may or may not be possible depending on how far out the inpainting mask outline was.
  30 Comments
Image Analyst
Image Analyst on 18 May 2014
So rather than avoid the problem, you just get values of infinity.
I doubt that there is much visible difference for small holes using any of those values.
What you said about Gaussian does not make sense. If there are no "good" pixels in the window, then there are no good pixels in the window and it makes absolutely no difference what the window values are.
Again, attach your image where it fails, and your code if you don't want me to keep guessing because you're making me work "blind". I don't think I've ever had a discussion on image processing go 30 replies without the poster ever even uploading an image.
Sepp
Sepp on 27 May 2014
Sorry for my late answer. I've solved the problem. I've made a small mistake and therefore it failed. Now it works perfectly. Again, thank you very much for your help.

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