%0 Journal Article
%T 一种基于加权图模型的手指静脉识别方法<br>A finger-vein recognition method based on weighted graph model
%A 叶子云
%A 杨金锋&lt
%A br&gt
%A YE Ziyun
%A YANG Jinfeng
%J 山东大学学报（工学版）
%D 2018
%R 10.6040/j.issn.1672-3961.0.2017.467
%X 摘要： 提出一种基于加权图模型的手指静脉网络特征描述方法。对于一幅手指静脉图像,通过图像划分获得图的顶点集,利用三角剖分获得图的边集,边的权重由边所连接顶点之间的特征相似度决定。通过这种方式,一幅手指静脉图像可转化为一个加权图,并通过度量加权图邻接矩阵之间的相似度实现手指静脉识别。详细研究影响识别结果的几个因素,并通过试验证明了该方法的有效性。<br>Abstract: A new weighted graph construction method was proposed for finger-vein network representation. For a weighted graph, its nodes and edges were respectively generated by dividing image into blocks and a triangulation algorithm, and the weights of edges were valued using the feature similarities between adjacent blocks. In this way, a finger-vein image could be represented by a weighted graph, and the adjacency matrix of this weighted graph was used for finger-vein recognition. The experiment results proved the effectiveness of the method, and some important factors that affected graph recognition results were discussed in detail
%K 加权图
%K 特征提取
%K 手指静脉识别
%K 图论
%K &lt
%K br&gt
%K finger-vein recognition
%K feature extraction
%K graph theory
%K weighted graph structure
%U http://gxbwk.njournal.sdu.edu.cn/CN/10.6040/j.issn.1672-3961.0.2017.467