摘要
提出一种改进的自适应距离保持水平集演化方法.该方法定义新的图像相依权系数与停止函数,有效解决了演化曲线对初始位置敏感的问题.零水平集曲线能根据图像性质自适应地决定向内还是向外运动,而且在像素灰度值相等的区域曲线能继续演化直至目标物体边界,并提高了零水平集曲线对深度凹陷边界的捕获能力.实验结果表明,该方法能有效检测目标边界,且有较强的抗噪能力.
In this paper,an improved method of adaptive distance preserving level set evolution is proposed.A weighting coefficient depending on information in the image and a stop function are defined.The evolution curve is no longer sensitive to the position of the initial curve,which can be anywhere in the image.The curve of zero level set can detect object boundaries when it is in a region with pixels having the same gray value.The method enhances capability of detecting boundary concavities.Experiments on images with different object boundaries show that the proposed method can detect the object contour effectively and has strong anti-noise ability.
出处
《应用科学学报》
EI
CAS
CSCD
北大核心
2011年第3期274-280,共7页
Journal of Applied Sciences
基金
国家自然科学基金(No.60970142)资助
关键词
图像分割
偏微分方程
几何活动轮廓
距离保持水平集方法
image segmentation
partial differential equation
geometric active contour mode
distance pre-serving level set method