Euclidean distance-ordered thinning for skeleton extraction

The skeleton is an important feature for the representation of a shape in image analysis. In this paper, we propose a novel Euclidean distance-ordered thinning algorithm for skeleton extraction. We first give the deletion templates which can determine a given pixel to be safely deleted or not from the pattern of its 8-neighbors. Then we delete the points which satisfy the deletion templates until there is no point that can be deleted in the linked lists of ascending order. Finally, the skeleton of the object is obtained. The experiment results show that the algorithm is able to extract the connected and one-pixel wide skeleton that can correctly preserve the topology of the object. Furthermore, the extracted skeleton locates on the accurate position and it is insensitive to boundary noise.

[1]  H. Blum Biological shape and visual science (part I) , 1973 .

[2]  Renato Perucchio,et al.  A topology-preserving parallel 3D thinning algorithm for extracting the curve skeleton , 2003, Pattern Recognit..

[3]  Edwin R. Hancock,et al.  A skeletal measure of 2D shape similarity , 2001, Comput. Vis. Image Underst..

[4]  Edwin R. Hancock,et al.  A Skeletal Measure of 2D Shape Similarity , 2001, IWVF.

[5]  Olaf Kübler,et al.  Hierarchic Voronoi skeletons , 1995, Pattern Recognit..

[6]  Cordelia Schmid,et al.  IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2004, Washington, DC, USA, June 27 - July 2, 2004 , 2004, CVPR Workshops.

[7]  Cecilia Di Ruberto,et al.  Recognition of shapes by attributed skeletal graphs , 2004, Pattern Recognit..

[8]  Frederic Fol Leymarie,et al.  Simulating the Grassfire Transform Using an Active Contour Model , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Kaleem Siddiqi,et al.  Flux invariants for shape , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[10]  Kaleem Siddiqi,et al.  Robust and efficient skeletal graphs , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[11]  V. T. Rajan,et al.  Voronoi diagrams of polygons: A framework for shape representation , 2004, Journal of Mathematical Imaging and Vision.

[12]  W. Eric L. Grimson,et al.  Fixed topology skeletons , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[13]  Chris Pudney,et al.  Distance-Ordered Homotopic Thinning: A Skeletonization Algorithm for 3D Digital Images , 1998, Comput. Vis. Image Underst..

[14]  Philip N. Klein,et al.  Recognition of shapes by editing their shock graphs , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Kin-Man Lam,et al.  Extraction of the Euclidean skeleton based on a connectivity criterion , 2003, Pattern Recognit..

[16]  Francis Y. L. Chin,et al.  Finding the Medial Axis of a Simple Polygon in Linear Time , 1995, ISAAC.

[17]  Sibel Tari,et al.  An axis-based representation for recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.