Face Recognition Based on Phase Only Correlation (POC)

E. S. Wahyuni, Faiz Khairul Isbat, Anggara Jatu Kusumawati
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Abstract

Face recognition is a technology that is widely used in the field of security and biometrics. Every human face has unique features such as the shape of the jaw and the contours of the face. In this study, face detection was carried out using the Phase Only Correlation (POC) method. POC is a face detection method based on the highest correlation value from the calculation of the phase and magnitude of an image. The data used in this study is in the form of facial images in RGB format. Stages of the study were divided into two, namely preprocessing and processing. The pre-processing stage includes the Region of Interest (ROI), image segmentation, grayscale transformation, and Discrete Fourier Transform (DFT). The processing phase includes Cross Spectrum, Inverse Cross Spectrum values, and correlation calculation. There are three testing schemes carried out in this study, namely testing of variations in lighting levels, expressions, and facial positions. From the results of the study, different face positions produce incorrect detection results because changes in the position of the image being tested make changes in the frequency distribution of the phase and magnitude values.
基于相位相关的人脸识别
人脸识别是一项广泛应用于安全和生物识别领域的技术。每个人的脸都有独特的特征,比如下巴的形状和脸部的轮廓。本研究采用纯相位相关(POC)方法进行人脸检测。POC是一种基于图像相位和幅值计算得出的最高相关值的人脸检测方法。本研究使用的数据为RGB格式的面部图像。研究阶段分为预处理和处理两个阶段。预处理阶段包括感兴趣区域(ROI)、图像分割、灰度变换和离散傅立叶变换(DFT)。处理阶段包括交叉谱、逆交叉谱值和相关计算。在本研究中有三种测试方案,即测试光照水平、表情和面部位置的变化。从研究结果来看,不同的人脸位置会产生不正确的检测结果,因为被测图像位置的变化会导致相位和幅度值的频率分布发生变化。
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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