吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (4): 732-738.

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基于面部边缘细节的局部遮挡人脸图像识别

李 炜    

  1. 武汉大学人民医院 信息中心, 武汉 430060
  • 收稿日期:2022-05-09 出版日期:2023-08-16 发布日期:2023-08-17
  • 作者简介: 李炜(1981— ), 男, 兰州人, 武汉大学人民医院工程师, 主要从事医疗数据应用及挖掘、 信息安全、 医院管理研究, (Tel)86-18971095881(E-mail)Niefenlgi@ whu. edu. cn。
  • 基金资助:
    国家自然科学基金资助项目(62172171) 

Image Recognition Method of Partial Occlusion Face Based on Facial Edge Details

 LI Wei    

  1. Information Center, Renmin Hospital of Wuhan University, Wuhan 430060, China
  • Received:2022-05-09 Online:2023-08-16 Published:2023-08-17

摘要: 为解决人物面部遮挡情况下识别人脸信息不清楚的缺陷, 优化人脸识别系统, 提出了基于面部边缘细节 的局部遮挡人脸图像识别方法。 依据稀疏性表达对人脸图像去噪, 根据图像灰度变换原理检测人脸图像边缘, 分割边缘区域, 计算其阈值以得到人脸图像边缘信息。 标记人脸特征点增强信息识别精度, 提取人脸图像的 特征描述子, 并将其输入支持向量机模型中, 通过训练实现局部遮挡人脸图像识别。 实验结果表明, 该方法 应用于人脸图像识别平均识别率高于 73% , 识别时间低于 20 s

关键词: 压缩感知, 图像的稀疏变换域, 区域阈值, 金字塔结构图, 高斯模糊差分

Abstract: In order to solve the problem of unclear face information in face recognition under face occlusion, and optimize the face recognition system, a local occlusion face image recognition method based on face edge details is proposed. The face image denoised according to the sparse expression, the edge of the face image is detected according to the principle of image gray transformation, the edge region is segment, and its threshold is calculated to obtain the edge information of the face image. The face feature is marked points to enhance the accuracy of information recognition, the feature descriptor of face image is extracted, it is input into support vector machine model, and local occlusion face image recognition is realized through training. The experimental results show that the average recognition rate of face image under the application of the proposed method is higher than 73% and the recognition time is less than 20 s. 

Key words: compressed sensing, sparse transform domain of images, regional threshold, pyramid structure map, Gaussian blur difference

中图分类号: 

  • TP391