Abstract: In this paper, a new algorithm of image segmentation based on the combination of the local
region and global region was proposed to solve the dependence of the initial contour on localizing
region-based active contour (LRAC) model. The algorithm combine the characteristics of Chan-Vese
model and LRAC model. When constructing the level set function, the variable weight parameters
were defined to combine the local and global energy functional terms of the level set function. Further,
the weight parameters were defined by image gradient and the mean of the inner and outer pixels at
the local image. In addition, the narrow band method was used in the evolution of the level-set
function to reduce the complexity of computation time. Experimental results show that our model has
the advantages of both CV model and LRAC model. Compared with LRAC model, the method we
proposed relies much less on the initial contour and has a better convergence rate. While compared
with CV model, the precision of our model is higher in the effect of target edge segmentation.

Key words: level set, image segmentation, active counter model, hybrid model, narrow band method