基于梯度向量流的活动轮廓模型  

Active Contour Model Based on Gradient Vector Flow

作　　者：罗岑弘[1] 

机构地区：[1]浙江财经大学艺术学院,浙江杭州310018

出　　处：《吉林大学学报（理学版）》2016年第5期1103-1108,共6页Journal of Jilin University:Science Edition

基　　金：国家教育信息技术研究"十二五"规划2015年度青年科研项目(批准号:156242644)

摘　　要：针对当前活动轮廓模型对噪声敏感,难实现弱边界图像的准确分割问题,提出一种基于梯度向量流的活动轮廓模型.首先采用Contourlet变换对图像进行去噪处理,解决了噪声对图像分割的干扰;然后在活动轮廓模型中引入一个指示函数,用于描述向量场与轮廓曲线间的关系,通过轮廓曲线演化过程实现图像分割;最后用实验对本文模型的图像分割性能进行验证.实验结果表明,该方法可以快速、准确地实现多种类型的图像分割,分割精度和抗噪能力优于其他活动轮廓模型.Aiming at the problem that the current active contour model was sensitive to noise,and it was difficult to realize accurate segmentation for weak boundary image,we proposed a new active contour model based on gradient vector flow.Firstly,contourlet transform was used to denoise image,and interference of noise to image segmentation was solved.Secondly,an instruction function was introduced to active contour model,which was used to describe the relationship between the vector field and the contour curve,and image was segmented by contour curve evolution.Finally,experiments were carried out to verify the performance of the proposed image segmentation model.Experimental results show that the proposed method can achieve fast and accurate segmentation for many kinds of images,and segmentation accuracy and anti noise ability are better than other active contour models.

关 键 词：梯度向量流 噪声敏感性 水平集 轮廓曲线 细节信息 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]