Rgb-d人脸识别采用lbp-dct算法

Q3 Economics, Econometrics and Finance Applied Computer Science Pub Date : 2021-09-30 DOI:10.35784/acs-2021-22
Sunil Kumar B L, S. M
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引用次数: 1

摘要

人脸识别是图像处理中识别或检查个人身份的应用之一。使用二维图像来识别人脸,但问题是这种图像对光线和不同视角的变化非常敏感。3D相机和立体相机拍摄的图像也可以用于识别,但需要相当长的处理时间。Kinect产生的RGB-D图像被用作3D图像的新替代方法。这种相机成本低,可以在任何情况和任何环境中使用。本文展示了基于RGB-D图像的人脸识别算法的性能。这些算法基于局部二进制模式计算使用RGB和深度图的描述符。这些图像也测试了LBP和DCT方法的融合。在实验中,LBP和DCT融合的识别率达到97.5%。
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RGB-D FACE RECOGNITION USING LBP-DCT ALGORITHM
Face recognition is one of the applications in image processing that recognizes or checks an individual's identity. 2D images are used to identify the face, but the problem is that this kind of image is very sensitive to changes in lighting and various angles of view. The images captured by 3D camera and stereo camera can also be used for recognition, but fairly long processing times is needed. RGB-D images that Kinect produces are used as a new alternative approach to 3D images. Such cameras cost less and can be used in any situation and any environment. This paper shows the face recognition algorithms’ performance using RGB-D images. These algorithms calculate the descriptor which uses RGB and Depth map faces based on local binary pattern. Those images are also tested for the fusion of LBP and DCT methods. The fusion of LBP and DCT approach produces a recognition rate of 97.5% during the experiment.
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来源期刊
Applied Computer Science
Applied Computer Science Engineering-Industrial and Manufacturing Engineering
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
8 weeks
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