提出一种新型、高效的基于B2DPCA(双向二维主成分分析)和ELM(极端学习机)的人脸识别算法,该算法是根据曲波变换分解人脸图像和一种改进的降维技术,通过B2DPCA生成识别特征集来训练和测试ELM分类器,提高识别精度.通过大量实验,并把实验结果与现存技术进行比较,结果表明B2DPCA+ ELM算法有效地提高了识别准确率,并降低了对原型数量的依赖.将来有望能把局部特征和基于曲波分解的全局信息结合起来应用到识别精度和分类速度上.
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