[1]冯小荣,惠康华,柳振东.基于卷积特征和贝叶斯分类器的人脸识别[J].智能系统学报,2018,13(5):769-775.[doi:10.11992/tis.201706052]
FENG Xiaorong,HUI Kanghua,LIU Zhendong.Face recognition based on convolution feature and Bayes classifier[J].CAAI Transactions on Intelligent Systems,2018,13(5):769-775.[doi:10.11992/tis.201706052]
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FENG Xiaorong,HUI Kanghua,LIU Zhendong.Face recognition based on convolution feature and Bayes classifier[J].CAAI Transactions on Intelligent Systems,2018,13(5):769-775.[doi:10.11992/tis.201706052]
基于卷积特征和贝叶斯分类器的人脸识别
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
13
期数:
2018年第5期
页码:
769-775
栏目:
学术论文—机器感知与模式识别
出版日期:
2018-09-05
- Title:
- Face recognition based on convolution feature and Bayes classifier
- Keywords:
- face recognition; convolutional neural network; pattern recognition; deep learning; Bayes classifier
- 分类号:
- TP393
- 摘要:
- 为解决传统人脸识别算法特征提取困难的问题，提出了基于卷积特征和贝叶斯分类器的人脸识别方法，利用卷积神经网络提取人脸特征，通过主成分分析法对特征降维，最后利用贝叶斯分类器进行判别分类，在ORL（olivetti research laboratory）人脸库上进行实验，获得了99.00%的识别准确率。实验结果表明，卷积神经网络提取的人脸图像特征具有很强的辨识度，与PCA（principal component analysis）和贝叶斯分类器结合之后可有效提高人脸识别的准确率。
- Abstract:
- To solve the difficulty of feature extraction of the traditional face recognition algorithm, a new method based on convolution feature and Bayes classifier is proposed, which uses convolution neural network to extract facial features and principal component analysis (PCA) to reduce the feature dimension, and finally, employs a Bayes classifier to classify the features. Experiments were carried out on the ORL face database, and a recognition accuracy of 99% was achieved. The experimental results show that the face features extracted by the convolution neural network have a strong degree of recognition. Therefore, the accuracy of face recognition in feature extraction can be effectively improved by combining PCA and Bayes classifier with convolution neural network.
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备注/Memo
收稿日期:2017-06-13。
基金项目:国家自然科学基金项目（U1233113，61571441）；中央高校基金项目（ZXH2012M005，3122014C016）；中国民航大学科研启动基金项目（2010QD10X）.
作者简介:冯小荣,男,1980年生,实验师,硕士研究生,主要研究方向为智能算法、图像处理。参与国家自然科学基金项目多项。发表学术论文 10余篇,其中被SCI、EI检索3篇;惠康华,男,1982年生,讲师,博士,主要研究方向为模式识别、计算机视觉、图像处理。参与国家自然科学基金项目多项。发表学术论文12篇,被SCI、EI检索6篇;柳振东,男,1992年生,硕士研究生,主要研究方向为模式识别、深度学习、图像处理。发表学术论文2篇。
通讯作者:惠康华.E-mail:khhui@cauc.edu.cn.
更新日期/Last Update:
2018-10-25