Image segmentation based on an improved CV model

Abstract:

In order to improve CV model’s performance on image with texture, we analyze the statistical properties of image texture components, and propose an improved segmentation algorithm. Specifically, this study has designed a new edge-preserving function based on the TV image smoothing. Also, the algorithm applies the CV model to segment the smooth component of an image. On the other hand, considering the fact that different smooth components have different segmentation areas, a new Smooth convergence function based on the region confidence is designed to overcome the disappearing of segmentation curve. Experimental results demonstrate that the proposed algorithm outperforms the traditional CV model in term of segmentation effects on natural images, but is insensitive to the inconsistent area.