Research of Face Image Recognition Based on Probabilistic Neural Networks

摘要：

This paper introduces the principle of probabilistic neural networks (PNN) algorithm and its application in face image recognition. After wavelet decomposition and discrete cosine transform, the image features of face image are extracted. Then the features are sent respectively into BP neural networks, LVQ neural networks and PNN neural networks for image recognition. ORL face image database is used in simulation experiments. Through analyzing and comparing the simulation results and recognition accuracy, conclusions are obtained of the advantage and characteristic of each neural networks. PNN neural networks show the highest recognition accuracy, thus it can be the optimal choice for image recognition.

关键词： Wavelet Decomposition Discrete Cosine Transform Probabilistic Neural Networks Face Image Recognition

作者: NI Qiakai GUO Chao YANG Jing

作者单位: College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024 College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024 Information Cen

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 3902-3905

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）