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Image segmentation Using Hybrid Level Set  

Joo Ki-See (목포해양대학교 해양운송시스템학부)
Kim Eun-Seok (아주대학교 산업공학과)
Abstract
The conventional image segmentation method using level set has been disadvantage since level set function in the gradient-based model evolves depending on the local profile of the edge. In this paper, a new model is introduced by hybridizing level set formulation and complementary smooth function in order to smooth the driving force. We consider an alternative way of getting the complementary function(CF) which is much easier to simulate and makes sense for most cases having no triple junctions. The rule of thumb is that CF must be computed such that the difference between their average and the original CF function should be able to introduce a reliable driving force for the evolution of the level set function. This proposed hybrid method tries to minimize drawbacks the conventional level set method.
Keywords
gradient-based model; complementary smooth function; hybridizing level set; driving force;
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