DocumentCode
318234
Title
On topological deep-structure segmentation
Author
Kalitzin, Stiliyan N. ; Romeny, Bart Ter Haar ; Viergever, Max
Author_Institution
Image Sci. Inst., Utrecht Univ., Netherlands
Volume
2
fYear
1997
fDate
26-29 Oct 1997
Firstpage
863
Abstract
A hierarchical segmentation model is obtained by using linear scale evolution of gray-scale images. At each scale segments are generated as Voronoi diagrams with a distance measure defined on the image landscape. The set of centers of the Voronoi cells is the set of local extrema of the gray-scale image. This set is localized by using the winding number distribution of the gradient vector field. Scale evolution induces hierarchical structure of embedded segments. Objects defined at coarser scales “decompose” into sub-objects at finer scales. The process is naturally described in terms of singularity catastrophes within the smooth scale evolution. Alternatively, we present a purely topological segmentation procedure, based on singular isophotes. The last are generated by the set of saddle points in the image which are detected also with the topological winding-number method
Keywords
catastrophe theory; computational geometry; image segmentation; topology; Voronoi cells; Voronoi diagrams; distance measure; gradient vector field; gray-scale images; hierarchical segmentation model; image segmentation; linear scale evolution; saddle points; singular isophotes; singularity catastrophes; topological deep-structure segmentation; winding number distribution; Diffusion processes; Euclidean distance; Gray-scale; Image segmentation; Joining processes; Kernel; Level measurement; Pattern analysis; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1997. Proceedings., International Conference on
Conference_Location
Santa Barbara, CA
Print_ISBN
0-8186-8183-7
Type
conf
DOI
10.1109/ICIP.1997.638633
Filename
638633
Link To Document