模糊积分混合n特征提取在人脸识别中的应用

J. Haddadnia, K. Faez
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引用次数: 1

摘要

本文介绍了一种基于RBF神经网络分类器的人脸识别方法,即混合n特征人脸识别(HNF)。提出了一种将RBF神经网络分类器与模糊积分相结合的人脸分类方法。特征提取器在每个适当选择的变换域中并行投影人脸图像。在ORL数据库上的实验结果表明,与现有的分类方法相比,该方法具有更高的分类精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid N-feature extraction with fuzzy integral in human face recognition
This paper introduces an efficient method for human face recognition that employs a set of different kinds of feature domains with RBF neural network classifiers, and which is denoted the hybrid N-feature (HNF) human face recognition. A combination of RBF neural network classifiers with fuzzy integral has been proposed to achieve face classification with higher performance. The feature extractor projects the face images in each appropriately selected transform domain in parallel. Experimental results on the ORL database confirm that the proposed method lends itself to higher classification accuracy relative to existing techniques.
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