一种结合CV与GAC模型的物体轮廓提取方法

A novel method for exacting object contour by combining CV model with GAC model

提出一种结合CV模型和GAC模型的方法,通过CV模型中长度项的权值调整,得到图像的两类分割.在此基础上,定义图像新的梯度,让GAC模型在新的梯度值空间搜索,从而得到物体的外部轮廓.在真实彩色图像上的实验结果表明,本算法能够大大改善CV模型在提取目标轮廓时的过分割问题,对物体内部不进行分割,并大大减少物体外部零星的小区域,收敛到目标物体的外部闭合轮廓.

In this paper a novel method combining CV model and GAC model is proposed to extractthe contours of the object. The method firstly adjusts the weight of the length in the CV model and getthe initial segmenting result. Then, a new gradient of the image is defined based on the initial segmen-ting result and introduced to the GAC model, which is used to extract the external contours of the ob-ject. Experimental results for real color images has shown that our method can greatly improve the per-formance of CV model for the over segmentation problem, and it also can converge to the externalclosed contuor of the object without segmenting the inner of the object and reducing the little scatteredregion outside the object.