Could someone point out the core texts or articles most useful on techniques for the removal of noise from scanned text for OCR applications?

  • 4
    $\begingroup$ While this is out of my area of expertise, that sounds like a very broad question. What sort of noise are you trying to remove? Dust present on the paper during the scan? Noise from the image sensor? Something else? Grayscale? Color? Monochrome? $\endgroup$
    – Jason R
    Commented Dec 3, 2011 at 1:42
  • $\begingroup$ They are black and white scans of old books with discolored pages and the pages end up with black small random shaped spots. $\endgroup$ Commented Dec 4, 2011 at 0:32

1 Answer 1


Google research has some excellent papers, see for example:

An Overview of the Tesseract OCR Engine

Also, it seems that stackoverflow has a similar question:


The most powerful image filtering techniques that I'm aware are graph-cuts based, which run in the following steps:

  1. Calculate a (sparse) distance matrix between pixels (based on their intensity)
  2. Spectral Clustering, keep only the lowest 3-8 eigenvectors
  3. K-means clustering of the eigenvectors

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