Application of Statistical Data Processing for Solving the Problem of Face Recognition by Using Principal Components Analysis Method

2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) Pub Date : 2019-01-01 DOI:10.1109/EICONRUS.2019.8657240

Wai Yan Min, Ekaterina L. Romanova, Yuri P. Lisovec, Aung Myo San

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引用次数: 9

Abstract

The system of face detection and recognition in the photo and video streams have been considered in this paper. Firstly, we took a number of images of each person to create our own database by using webcam. In these images, Viola-Jones algorithm is used for faces detection and then these images have been standardized and obtained our own database. The programs are implemented for modelling face recognition experiments by using the principal component analysis (PCA) method in MATLAB software environment. In this article, the statistical data processing method is used to improve the efficiency of facial recognition by using the principal components analysis. As a result of these experiments, more accurate results were obtained and the comparison results of face recognition before and after using the statistical data processing method are shown in this article. Experiments with other databases have confirmed the efficiency of statistical data processing.

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统计数据处理在主成分分析法人脸识别中的应用

本文研究了基于图像和视频流的人脸检测与识别系统。首先，我们给每个人拍了一些照片，用网络摄像头创建了我们自己的数据库。在这些图像中，我们使用Viola-Jones算法进行人脸检测，然后对这些图像进行标准化处理，得到我们自己的数据库。在MATLAB软件环境下，利用主成分分析(PCA)方法实现了人脸识别实验的建模程序。本文采用统计数据处理方法，通过主成分分析来提高人脸识别的效率。通过这些实验，得到了更加准确的结果，并给出了采用统计数据处理方法前后的人脸识别对比结果。与其他数据库的实验验证了统计数据处理的有效性。

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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2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)

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