This paper proposes a new region-based active contour for existing images segmentation model to light-sensitive. The energy functional consists of a geometric regularization term that penalizes the length of region boundaries and a data fitting term. Particularly

the local entropy is used as the data fitting term to distinguish different region. First

this paper uses a sliding window function to extract the local entropy according to the relationship of spatial arrangements of image pixel

which can map intensity space of image to local entropy space. Then

we can get the region competition model by maximum a posteriori segmentation probability in local entropy space. Next

it has a fuzzy region competition model by the membership function to replace the characteristic function to solving this model. Finally one can solve this model using fast Chambolle’s dual method. The experimental results for some images show desirable performances of this model

which has the fast convergence speed and light stability.