In this paper we introduce a new tool, called a pseudo-distance map (PDM), for extracting skeletons from grayscale images without region segmentation or edge detection. Given an edge-strength function (ESF) of a gray-scale image, the PDM is computed from the ESF using the partial differential equations we propose. The PDM can be thought of as a relaxed version of a Euclidean distance map. Therefore, its ridges correspond to the skeleton of the original gray-scale image and it provides information on the approximate width of skeletonized structures. Since the PDM is directly computed from the ESF without thresholding it, the skeletonization result is generally robust and less noisy. We tested our method using a variety of synthetic and real images. The experimental results show that our method works well on such images.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A pseudo-distance map for the segmentation-free skeletonization of gray-scale images


    Beteiligte:
    Jeong-Hun Jang, (Autor:in) / Ki-Sang Hong, (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    719444 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Pseudo-Distance Map for the Segmentation-Free Skeletonization of Gray-Scale Images

    Jang, J. / Hong, K. / IEEE | British Library Conference Proceedings | 2001



    A Segmentation-Free Approach for Skeletonization of Gray-Scale Images via Anisotropic Vector Diffusion

    Yu, Z. / Bajaj, C. / IEEE Computer Society | British Library Conference Proceedings | 2004


    Skeletonization of labeled gray-tone images

    Arcelli, C. / Serino, L. | British Library Online Contents | 2005