关键词: 图像分割, 活动轮廓, H1正则项, 偏微分方程, C-V模型

Abstract: Chan-Vese (C-V) model (CHAN T F, VESE L A. Active contours without edges. IEEE Transactions on Image Processing, 2001, 10(2): 266-277) is one of the well-known region-based image segmentation models. It is much less sensitive to the initialization of the contours and noise; however, the range of segmented images are not enough extensive. Therefore, through using the method of combining theoretical analysis with experiment and adding H1 regular term in C-V model, the algorithm was improved. A novel energy function for image segmentation was proposed, and an active contour model of region-based adaptive interpolation fit for a Partial Differential Equation (PDE) formulation was deduced. The experimental results show that the improved model can segment some images that C-V model is not applicable, and it is less sensitive to flexible initialization contours and significantly less sensitive to noise.

Key words: image segmentation, active-contour, H1 regular term, partial differential equation, Chan-Vese (C-V) model