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Proceedings Paper

Skeletonization And Distance Transformation By Greyscale Morphology
Author(s): Frank Y. Shih; O.Robert Mitchell
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Paper Abstract

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 struc-turing element. In order for this method to be useful for grey level images, a simple adaptive threshold algorithm using greyscale ero-sion with a non-linear structuring element has been developed.21 A decomposition technique which reduces the large size non-linear structuring element into a recursive operation with a small window allows real-time implementation.

Paper Details

Date Published: 22 March 1988
PDF: 7 pages
Proc. SPIE 0849, Automated Inspection and High-Speed Vision Architectures, (22 March 1988); doi: 10.1117/12.942827
Show Author Affiliations
Frank Y. Shih, Purdue University (United States)
O.Robert Mitchell, Purdue University (United States)


Published in SPIE Proceedings Vol. 0849:
Automated Inspection and High-Speed Vision Architectures
Rolf-Juergen Ahlers; Michael J. W. Chen, Editor(s)

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