We proposed a novel method to perform implicit modelling using the radial basis functions (RBFs), which is able to handle more complex topological changes, in particular perturbation away from the evolving front. This allows the initial contour or surface to be placed arbitrarily in the image. Compared to conventional level set based active models, our method has the following advantages:
Example results - complex topological changes
Initial Snake | Evolving Contours | Stabilised Snake | |
Conventional level set method | |||
Proposed method |
Example results - real image - horse
Conventional level set based active contour | |
Proposed method |
Example results - real image - flower
Conventional level set based active contour | |
Proposed method |
Example results - real image - brain
Conventional level set based active contour | |
Proposed method |
Example results - initialisation invariancy using the proposed method
Uniformly distributed circles | |
Parallel lines | |
No initialization |
Example results - more results using the proposed method
Example results - more results without initialisation using the proposed method
Example results by proposed method - 3D images
Initial deformable surface | Evolving deformable surface | Stabilised surface | Stabilised surface with inside hole |
Recovering object with arbitrary initialisation |
Recovering a complex 3D shape |
Publications