HVDLP : Horizontal Vertical Diagonal Local Pattern Based Face Recognition

Chandrakala, V. Kumar, K. Sureshbabu, B. RajaK
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Abstract

Face image is an efficient biometric trait to recognize human beings without expecting any co-operation from a person. In this paper, we propose HVDLP: Horizontal Vertical Diagonal Local Pattern based face recognition using Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The face images of different sizes are converted into uniform size of 108×990and color images are converted to gray scale images in pre-processing. The Discrete Wavelet Transform (DWT) is applied on pre-processed images and LL band is obtained with the size of 54×45. The Novel concept of HVDLP is introduced in the proposed method to enhance the performance. The HVDLP is applied on 9×9 sub matrix of LL band to consider HVDLP coefficients. The local Binary Pattern (LBP) is applied on HVDLP of LL band. The final features are generated by using Guided filters on HVDLP and LBP matrices. The Euclidean Distance (ED) is used to compare final features of face database and test images to compute the performance parameters.
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HVDLP:基于水平垂直对角局部模式的人脸识别
人脸图像是一种有效的生物特征特征,可以在不需要人的任何配合的情况下识别人。本文提出了一种基于水平垂直对角局部模式的人脸识别方法,该方法采用离散小波变换(DWT)和局部二值模式(LBP)。将不同大小的人脸图像转换为统一大小的108×990and预处理后将彩色图像转换为灰度图像。对预处理后的图像进行离散小波变换(DWT),得到大小为54×45的LL波段。该方法引入了HVDLP的新概念,提高了性能。将HVDLP应用于LL波段9×9子矩阵,考虑HVDLP系数。将局部二值模式(LBP)应用于LL波段的HVDLP。在HVDLP和LBP矩阵上使用引导滤波器生成最终特征。欧几里得距离(ED)用于比较人脸数据库和测试图像的最终特征,以计算性能参数。
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