摘要
用标号表示视差,建立能量函数,把匹配问题转化为能量函数最小化问题;通过构造网络,使能量与网络的割的容量相联系;利用图的网络流理论给出能量函数的最小化,从而获得图像匹配的视差数据.与目前已有基于图割的匹配算法相比,本算法将标号从1维向量推广到2维向量,适用于更一般情形下的视觉匹配,并且在全局上获得能量函数最小.实验结果表明,所提的匹配算法准确率较高.
Label is denoted by disparity and the energy fimction is established. Then the problem of matching can be transformed into that of energy function minimization. A network is constructed such that the energies can be related to the capacities of the cuts of the network. Finally, the minimal energy is obtained by the network-flows theory, and hence the disparity data are solved. Comparing with some known algorithms based on graph cuts, the algorithm in this paper extends the label from 1 dimension vector to 2 dimension vector, and adapts vision matching of more general conditions ;furthermore the algorithm can gain the minimization in global. Experimental results show that the algorithm has a high accuracy.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2006年第2期232-236,共5页
Acta Electronica Sinica
基金
国家自然科学基金(No.60473102)
安徽省教育厅自然科学重点基金(No.2005KJ005ZD)
安徽大学211工程学术创新团队基金
关键词
匹配
能量函数
图割
网络流
视差
matching
energy function
graph cuts
network flow
disparity
