基于机器视觉技术的红外与可见光人脸图像配准
Infrared and visible face image registration based on machine vision technology
王红梅 1曾国庆2
作者信息
- 1. 西南石油大学网络与信息化中心,成都 610000
- 2. 重庆移通学院通信与信息工程学院,重庆 401520
- 折叠
摘要
为解决某些环境图像中人脸轮廓模糊,人脸面部特征单一问题,提出基于机器视觉技术的红外与可见光人脸图像配准方法.采集红外与可见光人脸图像,对其进行直方图均衡化处理,采用Canny边缘算子方法提取人脸图像轮廓,并依据轮廓的梯度大小以及方向特征实现红外与可见光人脸图像配准.实结果表明:该方法可有效提升红外与可见光人脸图像的配准度,在无遮挡时配准度数值为0.961,在遮挡10％和20％时,配准度数值分别为0.949和0.944,由此说明该方法应用效果较为显著.
Abstract
In order to solve the problem of blurred face contour and single facial feature in some environment ima-ges,a method of infrared and visible light face image registration based on machine vision technology is proposed.Ac-quire infrared and visible face images,perform histogram equalization on them,use Canny edge operator method to ex-tract face image contour,and realize infrared and visible face image registration according to the gradient size and di-rection characteristics of the contour.The experimental results show that this method can effectively improve the regis-tration of infrared and visible face images.The registration value is 0.961 when there is no occlusion,and 0.949 and 0.944 when there is 10％and 20％occlusion,respectively.This shows that the application effect of this method is sig-nificant.
关键词
机器视觉/红外与可见光/人脸图像配准/图像采集卡/均衡化处理/轮廓提取Key words
machine vision/infrared and visible light/face image registration/image acquisition card/balanced processing/contour extraction引用本文复制引用
基金项目
重庆市教委科学技术研究项目(KJQN202102402)
出版年
2024
NETL
NSTL
万方数据