Skeletonization and distance transformation by greyscale morphology

Frank Y. Shih, O. Robert Mitchell

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Mathematical morphology applied to image processing which deals directly with shape is a more direct and faster approach to feature measurements than traditional techniques. It has grown to include many applications and architectures in image analysis. Binary morphology has been successfully extended to greyscale morphology which allows a new set of applications. In this paper, the distance transformation, skeletonization, and reconstruction algorithms using the greyscale morphology approach are described and proven to be remarkably simple. The distance transformation of an object is the minimum distance from inner points to the background of an object. The algorithm is a recursive greyscale erosion of the image with a small size structuring element. The distance can be Euclidean, chessboard, or city-block distance which depends on the selection of its structuring element. The skeleton extracted is the Medial Axis Transformation (MAT) which is produced from the result of the distance transformation. The values of the distance transform along the skeleton are maintained to represent distance to the closest boundary. We can easily reconstruct the distance transform from the skeleton by iterative greyscale dilations with the same structuring element. In order for this method to be useful for grey level images, a simple adaptive threshold algorithm using greyscale erosion with a non-linear structuring element has been developed. A decomposition technique which reduces the large size non-linear structuring element into a recursive operation with a small window allows real-time implementation.

Original languageEnglish (US)
Pages (from-to)80-86
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Mar 22 1988
Externally publishedYes
EventAutomated Inspection and High-Speed Vision Architectures 1987 - Cambridge, United States
Duration: Nov 2 1987Nov 6 1987

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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