Face Recognition Method Based on Artificial Neural Network

SHEN Ling-yun; LANG Bai-he; ZHU Ming

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Face Recognition Method Based on Artificial Neural Network

Imaging Technology & Image Processing | 更新时间：2020-08-12

- Face Recognition Method Based on Artificial Neural Network
- Chinese Journal of Liquid Crystals and Displays Vol. 26, Issue 6, Pages: 836-840(2011)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100049
  3. 长春理工大学电子信息工程学院,吉林长春,130022
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Received：23 June 2011，
  
  Revised：27 August 2011，
  
  Published Online：20 December 2011，
  
  Published：20 December 2011
- 稿件说明：
移动端阅览
沈凌云, 郎百和, 朱明. 一种基于人工神经网络的人脸识别方法[J]. 液晶与显示, 2011,26(6): 836-840

SHEN Ling-yun, LANG Bai-he, ZHU Ming. Face Recognition Method Based on Artificial Neural Network[J]. , 2011,26(6): 836-840
沈凌云, 郎百和, 朱明. 一种基于人工神经网络的人脸识别方法[J]. 液晶与显示, 2011,26(6): 836-840 DOI：

SHEN Ling-yun, LANG Bai-he, ZHU Ming. Face Recognition Method Based on Artificial Neural Network[J]. , 2011,26(6): 836-840 DOI：

摘要

提出了一种基于BP人工神经网络的人脸识别新算法。采用积分投影与几何特征提取相结合的方法进行人脸图像特征提取

构建特征向量

利用BP神经网络分类识别。仿真结果表明

该算法应用于ORL人脸库的分类识别

仅用13个特征即可达到平均识别率99%

识别能力显著增强

同时有效地降低了所需特征维数和计算复杂度。

Abstract

New method

back propagation neural network based face recognition was presented in this paper. The proposed method extracts feature from face image with differential projection and geometrical features into eigenvector which was classified by back propagation neural network. The experimental results on ORL face database show that the proposed method can achieve an average recognition accuracy of 99% by using only 13 features. Moreover

the identified power was enhanced effectively

and the computing complexity and feature dimensions were reduced greatly.

关键词

Keywords

references

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