A color image segmentation based on deep learning and level set

Abstract:

In this study, we combine the semantic segmentation technology based on full convolution neural network and image segmentation technology based on level set method and use Deeplab V2 and Distance Regularized Level Set Evolution (DRLSE) model to realize general color images segmentation. To improve the evolution speed of the zero level set segmentation, a new shape energy term is added to the DRLSE model. Numerical simulations verify the efficiency of our method.