Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/13464
Title: Impact of dehazing on underwater marker detection for augmented reality
Authors: Žuži, Marek 
Čejka, Jan 
Bruno, Fabio 
Skarlatos, Dimitrios 
Liarokapis, Fotis 
Keywords: Augmented reality;Dehazing;Image restoration;Markers;Tracking;Underwater images
Category: Computer and Information Sciences
Field: Natural Sciences
Issue Date: 14-Aug-2018
Publisher: Frontiers Media S.A.
Source: Frontiers Robotics AI, 2018, Volume 5, Issue AUG, Article number 92
Journal: Frontiers Robotics AI 
Abstract: Underwater augmented reality is a very challenging task and amongst several issues, one of the most crucial aspects involves real-time tracking. Particles present in water combined with the uneven absorption of light decrease the visibility in the underwater environment. Dehazing methods are used in many areas to improve the quality of digital image data that is degraded by the influence of the environment. This paper describes the visibility conditions affecting underwater scenes and shows existing dehazing techniques that successfully improve the quality of underwater images. Four underwater dehazing methods are selected for evaluation of their capability of improving the success of square marker detection in underwater videos. Two reviewed methods represent approaches of image restoration: Multi-Scale Fusion, and Bright Channel Prior. Another two methods evaluated, the Automatic Color Enhancement and the Screened Poisson Equation, are methods of image enhancement. The evaluation uses diverse test data set to evaluate different environmental conditions. Results of the evaluation show an increased number of successful marker detections in videos pre-processed by dehazing algorithms and evaluate the performance of each compared method. The Screened Poisson method performs slightly better to other methods across various tested environments, while Bright Channel Prior and Automatic Color Enhancement shows similarly positive results.
URI: http://ktisis.cut.ac.cy/handle/10488/13464
ISSN: 22969144
DOI: 10.3389/frobt.2018.00092
Rights: © 2018 Žuži, Čejka, Bruno, Skarlatos and Liarokapis.
Type: Article
Appears in Collections:Άρθρα/Articles

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