摘要
本课题利用了Gabor的良好鲁棒性和PCA降维方面的优势,提出了Gabor与PCA融合算法的人脸识别方法。Gabor小波变换适用于局部特征提取,该算法的鲁棒性优良,但需要多维度、多频率分解图像,增加了计算量,降低了识别率。PCA是一种降维算法,识别率高,融合Gabor与PCA算法能很好地提高人脸识别系统性能。本课题提出一种基于二者融合算法的人脸识别系统,并对该算法进行实验设计和实现。
In this subject,we propose a face recognition method based on the fusion of Gabor and PCA,which takes advantage of the robustness of Gabor and the dimensionality reduction of PCA.Gabor wavelet transform is suitable for local feature extraction,and the algorithm has good robustness,but it needs multi-dimensional and multi-frequency decomposition of the image,which increases the amount of calculation and reduces the recognition rate.This subject presents a face recognition system based on the fusion algorithm,and the experimental design and implementation of the algorithm.
作者
陈秀端
Chen Xiuduan(College of Mechanical Engineering,ZhangZhou Institute of Technology,Fujian Zhangzhou 363000)
出处
《南方农机》
2021年第18期139-142,共4页
基金
福建省中青年教师教育科研项目(JZ180802)。
