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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Improved Skeleton Extraction Based on Delaunay Triangulation
verfasst von : Jiayi Wei, Yingguang Hao, Hongyu Wang
Erschienen in: Communications, Signal Processing, and Systems
Verlag: Springer Singapore
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Abstract
The skeleton, which is the center axis of the target shape, is a topological representation of the shape. It has been used in image processing and pattern recognition fields such as target recognition, target matching, text recognition, blood vessel detection, and crack detection. Since Blum first used the grass burning model to extract the skeleton as a shape descriptor, there has been a lot of research on image skeleton extraction algorithms. In view of the problems existing in the existing methods, such as inaccurate skeleton position, discontinuous structure, and sensitivity to noise and small deformation, this paper proposes an improved image skeleton extraction algorithm based on constrained Delaunay triangulation, which effectively improves the performance of the algorithm by means of burr pruning, image pyramid, and other measures. The improved method can meet the requirements of object skeleton extraction in various scenes and has a good effect on noise suppression.