Based On The Variational Level Set Method For Multi-target Detection Model

Multiphase image segmentation/object detection is a field of the knowledge in Image Processing and Computer Vision,which has been widely used in biomedical image processing,scene interpretation,video image analysis and so on.It is paid great attention in Image Processing and Computer Vision due to the complexity on construction and modeling.It is convenient to set mathematical model based on Level Set Method for image segmentation.A novel variational level set method for multiphase object detection is presented in this paper,which uses n-l level set functions for n-l objects and background.The concept of geodesic active regions are used to region based active contour model which uses general probabilistic distribution functions.General characteristic functions of each regions are designed based on Heaviside functions of level set functions without overlapping and vacuum problems.The constraints of level set functions as signed distance functions are enforced in the functional to avoid re-initialization.The corresponding semi-implicit schemes are derived and used to some examples to validate the method suggested in this paper.