Face Recognition System Using Local Binary Pattern with Binary Dragonfly Algorithm to Feature Selection

Ahmed Raad Al-Aloosi, Hameed Mutlag Farhan, Raghda Awad Shaban Naseri, A. Turkben, Ahmed Khalid Mustafa, Mohammed G. F. Al-Obadi
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Abstract

In this paper, the local binary pattern is used to feature extraction, and the Binary Dragonfly Algorithm (BDA) is exploited to find the optimum features. This is a new methodology for face recognition systems. A proposed face acknowledgment framework was created to be utilized for various purposes. We utilized a local binary pattern for extraction of the important feature of the face that prepares the information and afterward, we utilized BDA to find the best features from feature data. We will execute and assess the proposed strategy on ORL and other datasets with MATLAB 2021a.
基于局部二值模式的人脸识别系统与二进制蜻蜓算法进行特征选择
本文采用局部二值模式进行特征提取,利用二进制蜻蜓算法(binary Dragonfly Algorithm, BDA)寻找最优特征。这是一种新的人脸识别方法。提出了一种人脸识别框架,可用于多种用途。我们利用局部二值模式提取人脸的重要特征,为信息做准备,然后利用BDA从特征数据中寻找最佳特征。我们将使用MATLAB 2021a在ORL和其他数据集上执行和评估所提出的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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