INFORMATION TECHNOLOGY FOR PERSON IDENTIFICATION BY FACE IMAGE IN CONDITIONS OF OCCLUSION

Author:

Zhabska Y.

Abstract

. Face recognition is a non-invasive biometric technology, so it is of interest both to owners of small surveillance systems and for national security purposes. State-of-the-art face recognition techniques have achieved impressive results with medium- and high-quality face images, but poor performance with low-quality images. The purpose of the study is to develop and experimentally verify the information technology of face identification based on the image of a face obtained from a video stream, based on an algorithm that provides high identification results on images of low quality and resolution that contain occlusion. This paper describes research of information technology of person identification by face image, which is based on an algorithm that includes anisotropic diffusion method for image preprocessing, Gabor wavelet transform for image processing, histogram of oriented gradients (HOG) and local binary patterns in 1- dimensional space (1DLBP) for extracting an image feature vector. Since the spread of the coronavirus disease has created the problem of facial recognition in the presence of a medical mask, which is used as a preventive measure, research on facial recognition and identification technologies has become crucial for all areas of cybersecurity based on digital identity verification. Experiments with the proposed technology after applying it to occluded images from the SCface database gave a result of 85%, which increased by 2.5% after converting the image format and resolution.

Publisher

National University of Life and Environmental Sciences of Ukraine

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference7 articles.

1. World Health Organization (2020). Mask use in the context of COVID-19: interim guidance. World Health Organization, 22.

2. M. Ngan, P. Grother and K. Hanaoka (2020). Ongoing Face Recognition Vendor Test (FRVT) Part 6A: Face recognition accuracy with masks using pre- COVID-19 algorithms. NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD. doi: 10.6028/NIST.IR.8311.

3. K. Hill (2022). Facial Recognition Goes to War. The New York Times. April 7, 2022. Available at: https://www.nytimes.com/2022/04/07/technology/facial-recognition-ukraine-clearview.html

4. J. Bhuiyan and agencies (2022). Ukraine uses facial recognition software to identify Russian soldiers killed in combat. The Guardian. March 24, 2022. Available at: https://www.theguardian.com/technology/2022/mar/24/ukraine-facial-recognition -identify-russian-soldiers

5. P. Perona and J. Malik. (1990). Scale-Space and Edge Detection Using Anisotropic Diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, No. 7, p. 629-639.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3