基于信号质量动态加权的多模生物特征识别研究

张闻彬; 刘培顺; 薛峰会

doi:10.11959/j.issn.2096-109x.2018022

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基于信号质量动态加权的多模生物特征识别研究

论文 | 更新时间：2024-06-03

- 基于信号质量动态加权的多模生物特征识别研究
- Multi-biometrics fusion based on dynamic weighting of characteristic signal quality
- 网络与信息安全学报 2018年4卷第3期页码：59-67
- 作者机构：
  
  1. 中国海洋大学信息科学与工程学院，山东青岛 266100
  2. 青岛黄海学院国际电子商务学院，山东青岛 266427
- 作者简介：
  
  [ "张闻彬（1994-），男，山东济南人，中国海洋大学硕士生，主要研究方向为信息安全、模式识别。 " ]
  [ "刘培顺（1975-），男，山东菏泽人，中国海洋大学讲师，主要研究方向为网络与信息安全。 " ]
  [ "薛峰会（1982-），男，山东沂水人，青岛黄海学院副教授，主要研究方向为网络与信息安全。 " ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key R＆D Plan Program of China(2017YFC0806200)
- DOI：10.11959/j.issn.2096-109x.2018022
  中图分类号： TP391.41
- 网络首发：2018-03，
  
  纸质出版：2018-03-15
- 稿件说明：
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张闻彬, 刘培顺, 薛峰会. 基于信号质量动态加权的多模生物特征识别研究[J]. 网络与信息安全学报, 2018,4(3):59-67.

Wenbing ZHANG, Peishun LIU, Fenghui XUE. Multi-biometrics fusion based on dynamic weighting of characteristic signal quality[J]. Chinese Journal of Network and Information Security, 2018, 4(3): 59-67.
张闻彬, 刘培顺, 薛峰会. 基于信号质量动态加权的多模生物特征识别研究[J]. 网络与信息安全学报, 2018,4(3):59-67. DOI： 10.11959/j.issn.2096-109x.2018022.

Wenbing ZHANG, Peishun LIU, Fenghui XUE. Multi-biometrics fusion based on dynamic weighting of characteristic signal quality[J]. Chinese Journal of Network and Information Security, 2018, 4(3): 59-67. DOI： 10.11959/j.issn.2096-109x.2018022.

摘要

将人脸识别和说话人识别进行决策层级的融合，为应对外界环境对识别结果的影响，引入图像质量和声音质量评价方法，通过对信息质量进行评估，去除信息质量较差的特征，根据信息质量动态调整模块的权重比例，并对单模特征识别匹配度低的个体做拒绝处理，然后根据D-S理论将各个证据合并成为一个新的证据体，实现对用户身份识别。实验结果显示，这种考虑特征信号质量的融合方法可以有效提升识别的准确率和安全性。

Abstract

Face recognition and speaker recognition were integrated at the decision-making level.In order to cope with the influence of the external environment on the recognition result

image quality and sound quality assessment methods were introduced.By evaluating the quality of information

features with poor information quality were removed.Information quality dynamically adjusted the weight proportion of the module

and rejected individuals with low matching degree of single-mode feature recognition.Then

according to DS theory

each evidence was merged into a new body of evidence to realize user identification.The experimental results show that the fusion method which takes into account the characteristic signal quality can effectively improve the recognition accuracy and security.

关键词

Keywords

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