基于外观的移动环境图像人脸识别方法

Abbas Memiş, F. Karabiber
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引用次数: 2

摘要

本文提出了一种基于外观的移动环境人脸识别系统,并对其性能进行了比较分析。在该系统中,人脸检测过程是通过对移动环境下的人脸图像使用类哈尔特征和级联分类器来完成的。对检测到的人脸图像进行色彩空间变换、维度归一化和直方图均衡化等预处理。采用主成分分析法、Fisher线性判别分析法和局部二值模式直方图法提取人脸特征。采用k近邻分类器对实现方法进行性能分析。在不同维度归一化的人脸图像上,测量并比较了所选人脸识别方法的准确率、精密度、召回率和f测量值。利用MOBIO人脸数据库进行的实验结果表明,局部二值模式直方图方法对移动环境图像具有较高的成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face recognition on mobile environment images using appearance based methods
In this paper, we present face recognition systems, which are performed by using appearance based methods on mobile environment face images, and their comparative performance analysis. In proposed systems, face detection process is performed by using Haar-like features and cascade classifiers on mobile environment face images. Color space transformation, dimensional normalization and histogram equalization operations are performed on detected face images as pre-processing steps. Principal Component Analysis, Fisher's Linear Discriminant Analysis and Local Binary Pattern Histograms methods are used to extract facial features. K-nearest neighbor classifier is employed for the performance analysis of implemented methods. Accuracy, precision, recall and F-measure values are measured and compared in performance evaluations of selected facial recognition methods on various dimensionally normalized face images. Experimental results obtained using MOBIO face database show that Local Binary Pattern Histograms method has high success rates on mobile environment images.
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