Information Technology for Person Identification by Occluded Face Image
Oleksii S. Bychkov, Kateryna Merkulova, Yelyzaveta Zhabska · 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) · 2022
This paper describes the research of information technology for person identification by occluded face image. As far as the spread of coronavirus disease (COVID-19) raised the problem of identification by facial image with masks covering the face as a prevention measure, the research of face recognition and identification technologies has become crucial for all of the cybersecurity areas based on the identity verification by digital technologies. The proposed algorithm, that is the cornerstone of the information technology, is based on the methods of anisotropic diffusion for image preprocessing, Gabor wavelet transform, histogram of oriented gradients (HOG) and local binary patterns in 1-dimensional space (1DLBP) for image feature vector extraction, and square Euclidean distance metric for vector classification. Experiments on the proposed technology after applying it on the occluded images from the SCface database provided the result of 85%, increased on 2.5% after image format and resolution conversion.