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Authors: Patricia Alejandra Pacheco Reina 1 ; 2 ; Armando Manuel Gutiérrez Menéndez 1 ; 2 ; José Carlos Gutiérrez Menéndez 1 ; 2 ; Graça Bressan 1 and Wilson Ruggeiro 1

Affiliations: 1 Laboratory of Computer Networks and Architecture, University of São Paulo, São Paulo, Brazil ; 2 Polytechnic School, University of São Paulo, São Paulo, Brazil

Keyword(s): Face Image Quality, Face Processing, Image Distortions.

Abstract: Face processing algorithms are becoming more popular in recent days due to the great domain of application they can be used in. As a consequence, research about the quality of face images is also increasing. Several papers concluded that image quality does impact the performance of face processing algorithms, with low-quality images having a detrimental effect on performance. However, there is still a need for a comprehensive understanding of the extent of the impact of specific distortions like noise, blur, JPEG compression, and brightness. We’ve conducted a study evaluating the performance of three face processing algorithms with images under different levels of the aforementioned distortions. The study’s results placed noise and blur with Gaussian distributions, as the main distortions affecting performance. A detailed description of the adopted methodology, as well as the results obtained from the study, is presented in this paper.

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Paper citation in several formats:
Reina, P.; Menéndez, A.; Menéndez, J.; Bressan, G. and Ruggeiro, W. (2021). Understanding the Impact of Image Quality in Face Processing Algorithms. In Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE; ISBN 978-989-758-511-1, SciTePress, pages 145-152. DOI: 10.5220/0010486501450152

@conference{improve21,
author={Patricia Alejandra Pacheco Reina. and Armando Manuel Gutiérrez Menéndez. and José Carlos Gutiérrez Menéndez. and Gra\c{C}a Bressan. and Wilson Ruggeiro.},
title={Understanding the Impact of Image Quality in Face Processing Algorithms},
booktitle={Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE},
year={2021},
pages={145-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010486501450152},
isbn={978-989-758-511-1},
}

TY - CONF

JO - Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE
TI - Understanding the Impact of Image Quality in Face Processing Algorithms
SN - 978-989-758-511-1
AU - Reina, P.
AU - Menéndez, A.
AU - Menéndez, J.
AU - Bressan, G.
AU - Ruggeiro, W.
PY - 2021
SP - 145
EP - 152
DO - 10.5220/0010486501450152
PB - SciTePress