吉林大学学报(信息科学版) ›› 2024, Vol. 42 ›› Issue (4): 683-689.

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基于改进 Gabor 算法的遮挡人脸智能识别方法

, 梁瑞   

  1. 西安翻译学院 信息工程学院, 西安 710105
  • 收稿日期:2023-05-05 出版日期:2024-07-22 发布日期:2024-07-22
  • 作者简介:王潇(1983— ), 女, 西安人, 西安翻译学院讲师, 主要从事计算机图像学研究, ( Tel)86-13572152344( E-mail) wxzw_1021 @ 163. com; 梁瑞(1987— ), 女, 西安人, 西安翻译学院副教授, 主要从事信号处理研究, ( Tel)86-15829260023( E-mail) liangrui2019@ 126. com。
  • 基金资助:

    陕西省教育厅科学研究计划基金资助项目(22JK0391)

Intelligent Recognition Method for Occluded Faces Based on Improved Gabor Algorithm

WANG Xiao, LIANG Rui   

  1.  School of Information Engineering, Xian FanYi University, Xian 710105, China

  • Received:2023-05-05 Online:2024-07-22 Published:2024-07-22

摘要:

为提高有遮挡人脸的识别精度, 提出基于改进 Gabor 算法的遮挡人脸智能识别方法。首先, 对人脸图像动态范围压缩, 并选择反锐化掩模滤波算法展开图像增强处理; 其次, 利用 Gabor 滤波器对信息保留较完整、亮度较高的半边脸进行特征提取; 最后将提取到的 Gabor 特征输入到极限学习机中完成遮挡人脸的智能识别。实验结果表明, 所提方法对处理遮挡人脸图像具有良好的效果, 且其对人脸图像识别具有精准度高、识别时间短等优点。

关键词: Gabor 算法, 反锐化掩模滤波算法, 特征提取, 极限学习机, 遮挡人脸识别

Abstract: To improve the recognition accuracy of occluded faces, an intelligent recognition method for occluded faces based on the improved Gabor algorithm is proposed. Firstly, the dynamic range of facial images is compressed and the anti sharpening mask filtering algorithm is selected for image enhancement processing. Secondly, Gabor filters are used to extract features from half faces with relatively complete information preservation and high brightness. Finally, the extracted Gabor features are input into an extreme learning machine to achieve intelligent recognition of occluded faces. The experimental results show that the proposed method has good processing performance for occluded facial images, and the processed facial image recognition has high accuracy and short recognition time.

Key words: Gabor algorithm, anti sharpening mask filtering algorithm, feature extraction, extreme learning machine, occlusive facial recognition

中图分类号: 

  • TP391