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Combining Local Binary Pattern and Local Phase Quantization for Face Recognition

机译:结合局部二值模式和局部相位量化进行人脸识别

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摘要

Combining information contained in image Spatial and frequency domains can provide rich important clues not seen in either individual of these domains. This paper presents a method of face recognition based on local binary pattern(LBP) and local phase quantization(LPQ). The face image is divided into several regions, LBP operator is used to extract LBP feature in the spatial domain and LPQ operator is used to extract LPQ feature in the frequency domain. Then concatenated into an enhanced feature vector to be used as a face descriptor. The simulation experiments illustrate that this method has better recognition rate and more robust than single method on the YALE and AR face database.
机译:合并包含在图像空间域和频域中的信息可以提供丰富的重要线索,这些线索在这些域的任何一个中都没有。本文提出了一种基于局部二进制模式(LBP)和局部相位量化(LPQ)的人脸识别方法。人脸图像被分为几个区域,LBP运算符用于在空间域中提取LBP特征,而LPQ运算符用于在频域中提取LPQ特征。然后连接到增强的特征向量中,用作人脸描述符。仿真实验表明,在YALE和AR人脸数据库上,该方法比单一方法具有更好的识别率和鲁棒性。

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