Comments on: Cleaning up scanned text – revisited http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/ Steve Eddins manages the Image & Geospatial development team at The MathWorks and coauthored Digital Image Processing Using MATLAB. He writes here about image processing concepts, algorithm implementations, and MATLAB. Sat, 11 Feb 2012 18:27:50 +0000 hourly 1 http://wordpress.org/?v=3.2.1 By: Steve http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-18960 Steve Mon, 21 Jan 2008 13:45:10 +0000 http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-18960 Greg—Thanks for your suggestions. Greg—Thanks for your suggestions.

]]> By: Greg http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-18660 Greg Tue, 15 Jan 2008 06:29:37 +0000 http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-18660 Look up the work on reconstructing FAX images which essentially do the following: 1) Break the fax into glyphs (i.e, each character) 2) Find the glyphs that nearly match each other 3) Combine glyphs that nearly match each other (a simple naive method is to average the glyphs and then threshold the result) 4) Put the glyphs back on the page in their original location This is quite similar to the lossy JBIG2 compression algorithm. Another approach is to use a vertical median filter where each pixel in an X pixel (usually 5 or 7) vertical line is set to the median value of the X pixels. This preserves vertical lines and fills in 1 pixel gaps. Follow that with a horizontal median filter to fill in gaps in horizontal lines. Look up the work on reconstructing FAX images which essentially do the following:
1) Break the fax into glyphs (i.e, each character)
2) Find the glyphs that nearly match each other
3) Combine glyphs that nearly match each other (a simple naive method is to average the glyphs and then threshold the result)
4) Put the glyphs back on the page in their original location

This is quite similar to the lossy JBIG2 compression algorithm.

Another approach is to use a vertical median filter where each pixel in an X pixel (usually 5 or 7) vertical line is set to the median value of the X pixels. This preserves vertical lines and fills in 1 pixel gaps. Follow that with a horizontal median filter to fill in gaps in horizontal lines.

]]> By: Steve http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-17578 Steve Wed, 26 Dec 2007 14:40:28 +0000 http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-17578 Ian—Use <tt>hold on</tt> and <tt>plot</tt> to superimpose lines on top of an image. See <a href="http://blogs.mathworks.com/steve/2007/01/01/superimposing-line-plots/" rel="nofollow">this post</a> for examples. Ian—Use hold on and plot to superimpose lines on top of an image. See this post for examples.

]]> By: ian http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-17344 ian Sun, 23 Dec 2007 06:41:57 +0000 http://blogs.mathworks.com/steve/2007/12/21/cleaning-up-scanned-text-revisited/#comment-17344 Thanks for the block.Hopefully I will be doing OCR if all goes well. Sorry to use thiss forum but I have spend 4 hours trying to figure out a solution.Checking online and trying in matlab. Am trying to a rectangular around every labelled component in the image.However I can't figure out how to do this using BoundingBox the documentation gives a brief mention. Pointing me the right direction would help. I tried following the syntax of adding a centroid to the image but even that was failure. Thanks for the block.Hopefully I will be doing OCR if all goes well. Sorry to use thiss forum but I have spend 4 hours trying to figure out a solution.Checking online and trying in matlab. Am trying to a rectangular around every labelled component in the image.However I can’t figure out how to do this using BoundingBox the documentation gives a brief mention. Pointing me the right direction would help. I tried following the syntax of adding a centroid to the image but even that was failure.

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