A variationally based weighted re-initialization method for geometric active contours
Susana Merino‐Caviedes, G. Vegas-Sanchez, Maria Teresa Perez, Santiago Aja‐Fernández, Marcos Martín‐Fernández
Abstract
Susana Merino‐Caviedes, G. Vegas-Sanchez, Maria Teresa Perez, Santiago Aja‐Fernández, Marcos Martín‐Fernández
Abstract
In geometric active contour algorithms, a re-initialization step must be performed by the level set function to remain close to a signed distance function, in order to avoid numerical instabilities. We propose a new re-initialization method that may be employed as a standalone method to recover the signed distance condition, or may be embedded directly into a variational framework as an additional term for the energy functional. Its purpose is to make the pixels near the propagating contour be less affected by the re-initialization. Experimental results show that whereas previous approaches change the position of the zero level set, our method keeps it virtually unchanged.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In geometric active contour algorithms, a re-initialization step must be performed by the level set function to remain close to a signed distance function, in order to avoid numerical instabilities. We propose a new re-initialization method that may be employed as a standalone method to recover the signed distance condition, or may be embedded directly into a variational framework as an additional term for the energy functional. Its purpose is to make the pixels near the propagating contour be less affected by the re-initialization. Experimental results show that whereas previous approaches change the position of the zero level set, our method keeps it virtually unchanged.
Key concepts: Initialization, Signed distance function, Position (finance), Level set (data structures), Active contour model, Pixel, Computer science, Function (biology)