Geometric Deformable Models with Topology Analysis for Shape Modeling

B. Yang and M. Allili (Canada)


geometric deformable model, level set method, digital topology, topology analysis, shape recovery, object detec tion


A key issue in object recognition using the shape of the ob ject’s boundary and surface reconstruction using slice con tours is the ability to identify the complete boundaries of the segmented objects in the scene. Geometric deformable models(GDM) using the level set method provide a very efficient framework for image segmentation. However, the segmentation results provided by these models are usually dependent on the contour initialization, and in most cases where the strategy is to detect all the scene objects, the re sults of the segmentation will only provide partial objects boundaries. In this work, we propose a method based on digital topology that will allow in certain cases to detect the complete boundary information of the segmented objects. This information turns out to be very crucial in carrying out a topological analysis of the objects and can be used in their higher level processing as outlined previously.

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