Visual Form pp 249-258 | Cite as

Fast Thinning Algorithms for Large Binary Images

  • Christian Evers


Image resolutions of 100002 pixels or more are required if we scan large engineering drawings or maps to convert them to CAD-data. An important preprocessing step for the vectorization of the scanned lines is thinning them to minimal width for line-following. Most thinning algorithms are suitable for small resolutions only. We present two fast algorithms for thinning large binary images. The first one is a variation of an iterative parallel thinning algorithm. For most images it requires only one scan through the image matrix. The second method requires two forward scans through the image matrix, regardless of the thickness of the scanned lines.


Interior Point Binary Image Symmetry Point Image Segment Image Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Christian Evers
    • 1
  1. 1.Corporate Research and Development, ZFE IS INF 11Siemens AGMünchen 83Germany

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