ACS Applied Computer Science

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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.



  • APA 7th style
Sunil Kumar, B. L., & Sharmila Kumari, M. (2021). RGB-D face recognition using LBP-DCT algorithm. Applied Computer Science, 17(3), 73-81.
  • Chicago style
Sunil Kumar, B. L., and M. Sharmila Kumari. "Rgb-D Face Recognition Using Lbp-Dct Algorithm." Applied Computer Science 17, no. 3 (2021): 73-81.
  • IEEE style
B. L. Sunil Kumar and M. Sharmila Kumari, "RGB-D face recognition using LBP-DCT algorithm," Applied Computer Science, vol. 17, no. 3, pp. 73-81, 2021, doi: 10.23743/acs-2021-22.
  • Vancouver style
Sunil Kumar BL, Sharmila Kumari M. RGB-D face recognition using LBP-DCT algorithm. Applied Computer Science. 2021;17(3):73-81.