Automated visual inspection algorithm for the reflection detection and removing in image sequences
Author(s) -
Roman Sizyakin,
Viacheslav Voronin,
Nikolay Gapon,
Alexey B. Nadykto,
Aleksandra Pižurica,
Alexander Zelensky
Publication year - 2020
Publication title -
ghent university academic bibliography (ghent university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1117/12.2559362
Subject(s) - specular reflection , computer vision , computer science , specular highlight , artificial intelligence , brightness , reflection (computer programming) , image (mathematics) , algorithm , optics , physics , programming language
Specular reflections are undesirable phenomena that can impair overall perception and subsequent image analysis. In this paper, we propose a modern solution to this problem, based on the latest achievements in this field. The proposed method includes three main steps: image enhancement, detection of specular reflections, and reconstruction of damaged areas. To enhance and equalize the brightness characteristics of the image, we use the alpha-rooting method with an adaptive choice of the optimal parameter-alpha. To detect specular reflections, we apply morphological filtering in the HSV color space. At the final stage, there is a reconstruction of damaged areas using adversarial neural networks. This combination makes it possible to quickly and effectively detect and remove specular reflections, which is confirmed by a series of experiments given by the experimental section of this work.
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