| 一种基于矢量阈值的自适应图像分割方法 |
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| 引用本文： | 汤可宗,张磊,高尚.一种基于矢量阈值的自适应图像分割方法[J].昆明理工大学学报(理工版),2007,32(5):23-26. |
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| 作者姓名： | 汤可宗 张磊 高尚 |
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| 作者单位： | 1. 江苏科技大学,电子信息学院,江苏,镇江,212003;苏州大学,江苏省计算机信息处理技术重点实验室,江苏,苏州,215006
2. 江苏科技大学,电子信息学院,江苏,镇江,212003 |
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| 基金项目： | 江苏省计算机信息处理技术重点实验室开放课题基金资助项目(KJS0601)，江苏省“青蓝工程”资助 |
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| 摘 要： | 针对灰度图像,提出一种基于空间特征矢量的图像分割方法,分割前首先对边缘进行增强处理,并构建以像素的灰度、梯度、像素邻域均值为特征的三维特征空间.将图像像素点引入对应于空间特征点.通过计算像素特征矢量与特征矢量阈值的差矢量,求出矢量差与特征矢量阈值的夹角,比较夹角与动态分割参数的关系,以判定像素所在区域(目标或背景).实验表明,该方法能较快的实现图像分割,分割的效果也较好.
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| 关 键 词： | 图像分割 直方图 灰度图像 |
| 文章编号： | 1007-855X（2007）05-0023-04 |
| 修稿时间： | 2007-06-07 |
A Self-adaptive Method of Image Segmentation Based on Vector Threshold |
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| TANG Ke-zong,ZHANG Lei,GAO Shang.A Self-adaptive Method of Image Segmentation Based on Vector Threshold[J].Journal of Kunming University of Science and Technology(Natural Science Edition),2007,32(5):23-26. |
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| Authors: | TANG Ke-zong ZHANG Lei GAO Shang |
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| Affiliation: | 1. Scholol of Electrics and Information, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China; 2. Soochow University,Jiangsu Provincial Key Laboratory of Computer Information Processing Technology,Suzhou, Jiangsu 215006, China |
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| Abstract: | As to the gray image,a new method of image segmentation based on space feature vector is presented.Its procedures are mainly divided into three steps.Firstly,Edge is strengthened before image segmentation,and a feature space with three dimensions based on gray,gradient,pixels neighborhood is constructed in advance.Ever pixels in image is related to a feature point in the space.Edge is strengthened before segmentation.Secondly,computing the vector differences between feature vector and feature threshold vector,and the angle between difference vector and feature vector threshold can be obtained.Finally,comparing its angle with segmentation parameter one,the region(target or background) of pixels can be determined.According to experimental results,it is an effective and accurate method in image segmentation. |
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| Keywords: | image segmentation histogram grey inmage |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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