[1]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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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
13
Number of periods:
2018 5
Page number:
769-775
Column:
学术论文—机器感知与模式识别
Public date:
2018-09-05
- Title:
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Face recognition based on convolution feature and Bayes classifier
- Author(s):
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FENG Xiaorong; HUI Kanghua; LIU Zhendong
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School of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China
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- Keywords:
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face recognition; convolutional neural network; pattern recognition; deep learning; Bayes classifier
- CLC:
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TP393
- DOI:
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10.11992/tis.201706052
- Abstract:
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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.