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一种煤矿井下复杂光照条件下的人脸识别方法

Face Recognition Method Under Complex Light Conditions in Coal Mines

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摘要

为了解决煤矿井下复杂光照条件导致人脸识别率低的问题, 提出了一种适用于煤矿井下复杂光照条件下的人脸识别方法。首先利用小波分解将人脸图像分解为低频和高频部分, 对低频部分利用直方图均衡化处理, 增强图像对比度; 然后采用引入模糊隶属度因子的小波去噪模型对高频部分进行滤波处理, 并通过新的PAL模糊增强算法对高频部分进行模糊增强, 在不同阈值下的非线性变换得到不同尺度、不同方向的特征图像, 并进行反模糊处理; 最后对处理后的低频和高频部分进行小波重构。实验表明, 在井下复杂光照条件下, 本文提出的人脸识别方法能有效改善人脸图像的整体效果, 增强图像的细节信息, 且平均识别率能够达到94.45%, 显著提高了井下复杂光照下的人脸识别率。

Abstract

In order to solve the problem of low face recognition rate caused by the complex lighting conditions in coal mines, a face recognition method applied to the underground coal mines with complex lighting conditions is proposed. First, the face image is decomposed into low-frequency and high-frequency components by wavelet decomposition, and simultaneously the histogram equalization processing is conducted on the low-frequency components to enhance the image contrast. Then, the wavelet denoising model with a fuzzy degree of membership factor is used to filter the high-frequency components and meanwhile a new PAL fuzzy enhancement algorithm is adopted for the fuzzy enhancement of high-frequency components. Under different thresholds, a non-linear transformation is used to get feature images with different scales and different directions, and the anti-fuzzy processing is conducted. Finally, the processed low-frequency and high-frequency components are reconstructed based on wavelets. The experimental results show that the proposed face recognition method can be used to effectively improve the overall effect of face images and enhance the detail information of images under the complex lighting conditions in underground coal mines. Moreover, the average recognition rate can reach 94.45%, indicating the face recognition rate under complex lighting conditions in coal mines is significantly enhanced.

Newport宣传-MKS新实验室计划
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中图分类号:TN911.73

DOI:10.3788/lop56.011003

所属栏目:图像处理

基金项目:国家重点研发计划(2017YFC0804300, 2016YFC0801800)

收稿日期:2018-05-26

修改稿日期:2018-06-26

网络出版日期:2018-07-18

作者单位    点击查看

霍跃华:中国矿业大学(北京)现代教育技术中心, 北京 100083
范伟强:中国矿业大学(北京)机电与信息工程学院, 北京 100083

联系人作者:范伟强(fan_weiqiang@163.com)

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引用该论文

Huo Yuehua,Fan Weiqiang. Face Recognition Method Under Complex Light Conditions in Coal Mines[J]. Laser & Optoelectronics Progress, 2019, 56(1): 011003

霍跃华,范伟强. 一种煤矿井下复杂光照条件下的人脸识别方法[J]. 激光与光电子学进展, 2019, 56(1): 011003

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