基于梯度向量流的活动轮廓模型

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.

Active Contour Model Based on Gradient Vector Flow

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.