Skeletonization based on error reduction

Paul Morrison, Ju Jia Zou

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    The accuracy of a non-pixel-based skeletonization method is largely dependent on the contour information chosen as input. When using a Constrained Delaunay Triangulation to construct an object's skeleton, a number of contour pixels must be chosen as a basis for triangulation. This paper presents a new method of selecting these contour pixels. A new method for measuring skeletonization error is proposed, which quantifies the deviation of a skeleton segment from the true medial axis of a stroke in an image. The goal of the proposed algorithm is to reduce this error to an acceptable level, whilst retaining the superior efficiencies of previous non-pixel-based techniques. Experimental results show that the proposed method is adept at following the medial axis of an image, and is capable of producing a skeleton that is confirmed by a human's perception of the image. It is also computationally efficient and robust against noise.
    Original languageEnglish
    Number of pages11
    JournalPattern Recognition
    Publication statusPublished - 2006

    Keywords

    • constrained Delaunay triangulation
    • image processing
    • medial axis
    • skeletonization
    • thinning

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