摘要
针对灰度不均匀图像分割提出了一种自适应灰度值的图像分割方法,该方法基于水平集理论,结合目标图像和背景的灰度值信息,将全局与局部信息进行自适应线性拟合,然后进行图像分割,避免分割陷入局部最优,对噪声具有很好的鲁棒性。实验表明,该方法能够有效地抵抗噪声干扰,可以自适应图像不均匀灰度信息,对图像进行分割,可得到全局最优分割。
Aiming at segmentation to images with nonuniform gray-level, an image segmentation method adaptive to gray value was proposed. Based on the level set theory, by using the gray value information of target image and the background, adaptive linear fitting was made to the global and local information. Then, image segmentation was conducted to avoid being trapped in the local optimum, which was robust to noise. The experimental results showed that the proposed method can resist noise effectively, is adaptive to the nonuniform gray level information, and can obtain global optimal image segmentation.
作者
张爱丽
孙茂泽
刘团宁
ZHANG Ai-li SUN Mao-ze LIU Tuan-ning(College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China Engineering Lab of Henan Province for Intelligence Business ＆ Internet of Thing, Xinxiang 453007, China)
出处
《电光与控制》
北大核心
2016年第10期27-30,共4页
Electronics Optics & Control
基金
国家自然科学基金(U1204606
61173071)
河南省教育厅科学技术研究重点项目(13A510533)
关键词
图像分割
灰度不均匀信息
全局分割
自适应拟合
image segmentation
nonuniform gray-level information
global segmentation
adaptive fit
