基于B2DPCA和极端学习机的人脸识别

介绍一种新的基于双向二维主成分分析(B2DPCA)和极端学习机(ELM)的人脸识别方法,该方法是根据人脸曲波图像分解和一种改进的降维技术,通过B2DPCA生成识别特征集来提高分类精度.该方法还能够有效地提高分类正确率和降低对原型数量的依赖.通过做大量的实验,把结果和现存技术相比较.

Human Face Recognition Based on B2DPCA and ELM

In this work,a new human face recognition algorithm based on bidirectional two dimensional principal component analysis(B2DPCA) and extreme learning machine(ELM) is introduced.The proposed method is based on curvelet image decomposition of human faces and an improved dimensionality reduction technique. Discriminative technique.Discriminative feature sets are gener- ated using B2DPCA to ascertain classification accuracy. Other notable contr-ibutions of the proposed work include significant improvements in classification rate, up to reduction in traini- ng time and minimal dependence on the number of prototypes. Ex- tensive experiments are performed using databases and results are compared against state of the art techniques.