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

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    $\begingroup$ 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 Dec 3 '11 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. $\endgroup$ – Harry Spier Dec 4 '11 at 0:32
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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:

https://stackoverflow.com/questions/4180629/ocr-and-image-preprocessing-techniques

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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