Aiming at the problem of unsatisfactory image segmentation effect for images with blurred boundary by using traditional algorithms, a coarse-to-fine approach for image boundary extraction is proposed in this paper, which is made up of pixel coverage segmentation and Chan-Vese model. Based on modified coverage segmentation algorithm and active-contours method, images are firstly segmented by using the original coverage segmentation algorithm and a multi-directions fuzzy morphological boundary detection algorithm is used to extract the boundaries between different objects. Then an improved pixel coverage segmentation method is applied to redistribute coverage values for boundary pixels. Finally, the boundary extraction for refined images is carried out with active-contours algorithm. And qualitative comparison of segmentation results, noise immunity tests and contrast experiments on the extracted boundary are carried out. Experimental results show that the proposed method can obtain more excellent boundary extraction effect than those state-of-the-art methods proposed in comparable literatures.