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Position: Home > Articles > Research on Color Trees Image Segmentation Journal of West China Forestry Science 2014 (6) 33-38

彩色树木图像分割算法的研究

作  者：
白雪冰;郭景秋;陈凯;祝贺;张庭亮
单  位：
东北林业大学机电工程学院
关键词：
彩色图像分割;C-V模型;形态学处理;分水岭;最大熵
摘  要：
树木图像分割是将树木与其周围景物分离的技术,是虚拟现实和计算机仿真等学科在林业应用的核心技术,也是机器视觉领域的重要研究方向,拓宽了计算机技术在林业中的应用。本项研究基于树木图像形状复杂的特点,设计并实现了一种结合C-V模型水平集及形态学处理的彩色树木图像分割算法。运用改进的最小化能量函数作为水平集的演化曲线,可以更加自然地改变曲线拓扑结构,对含有分裂、合并、形成尖角等复杂形状的目标对象分割更为有效。如果再结合形态学后处理算法,将初次分割图像中非目标区的细密纹理和噪声剔除,可以快速准确地得到全局最优的图像分割效果。同时进行了与基于梯度变换的改进分水岭树木图像分割和基于灰度-梯度最大熵的树木图像分割算法的对比试验,试验表明,结合C-V模型水平集和形态学算法对树木图像分割效果更为有效。
译  名：
Research on Color Trees Image Segmentation
作  者：
BAI Xue-bing;GUO Jing-qiu;CHEN Kai;ZHU He;ZHANG Ting-liang;College of Electromechanical Engineering of Northeast Forestry University;
关键词：
color image segmentation;;C-V model;;later morphological processing operation;;watershed;;the maximum entropy
摘  要：
The trees image segmentation is a technology separating trees from its surrounding landscape,which is the core technology in virtual reality and computer simulation of forestry application and also is one of the focus areas in machine vision to provide basic data and technical support for the application of computer technology in forestry. Base on characteristics of complex shapes of the trees image,this paper designed and implemented a color image segmentation based on a set level of C-V model and later morphological processing operation. The improved minimization of energy function was made as the level set evolution curve,because it could naturally change the evolution curve,and also more effectively segment complex shapes with parts of fission,mergence and sharp corner.Then combined with the later morphological processing operation,which could clear the non- target parts such as texture and noise from the initial image segmentation,finally the global optimal image segmentation could be obtained fast and accurately. At the same time,we compared the color trees image segmentation,combined with a set with level of C-V model and the later morphological processing operation,with the improved watershed trees image segmentation based on gradient transform and the maximum entropy trees image segmentation based on gray gradient. The results showed that the method combined a set level of C-V model and the later morphological processing operation was more effective.

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