Design of face recognition system based on fuzzy transform and radial basis function neural networks

被引：0
|
作者：
Seok-Beom Roh
Sung-Kwun Oh
Jin-Hee Yoon
Kisung Seo
机构：
[1] The University of Suwon,Department of Electrical Engineering
[2] Sejong University,School of Mathematics and Statistics
[3] Seokyeong University,Department of Electronic Engineering
来源：
Soft Computing | 2019年 / 23卷
关键词：
Fuzzy C-means clustering (FCM clustering); Fuzzy transform (F-transform); Fuzzy radial basis function neural networks (FRBFNNs); Preprocessing technique;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this study, a face recognition method based on fuzzy transform and radial basis function neural networks is proposed. In order to reduce the dimensionality and extract the important features of face images, fuzzy transform with fuzzy partition techniques is used. Fuzzy radial basis function neural networks (FRBFNNs) are used as a classifier to identify face images into several categories. Radial basis functions are defined by fuzzy C-means clustering method which can analyze the distribution of data points over the input spaces. In order to validate the proposed face recognition system, experimental comparative studies are conducted on the benchmark face datasets such as YALE, ORL, and ABERDEEN databases. A comparative analysis demonstrates that the proposed face recognition system is superior to the conventional face recognition techniques.
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收藏
页码：4969 / 4985
页数：16
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