Research on Level Set Based on CV Model for Spatial Multi-target Recognition

The edgeless active contour model can solve the initialization problem, noise problem and boundary leakage problem, but due to the use of level sets, there are still problems of low computational efficiency and difficult implementation. Combining the global effect of CV model and the local effect of RSF, this paper establishes a global and local biphasic level set model based on CV-RSF by setting weight coefficients and introducing bilevel set. By increasing the energy penalty term, the level set function maintains an approximate signed distance function during the evolution process. The comparison experiments with other level set models show that the segmentation efficiency and accuracy of this model are improved.