A new approach to turbid water surface identification for autonomous navigation
Files
Date issued
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Václav Skala - UNION Agency
Abstract
Navigation of autonomous vehicles in natural environments based on image processing is certainly a complex
problem due to the dynamic characteristics of aquatic surfaces, such as brightness and color saturation. This
paper presents a new approach to identify turbid water surfaces based on their optical properties, aiming to allow
automatic navigation of autonomous vehicles regarding inspection, mitigation and management of aquatic natural
disasters. More specifically, computer vision techniques were employed in conjunction to artificial neural networks
(ANNs), in order to build a classifier designed to generate a navigation map that is interpreted by a state machine
for decision making. To do so, a study on the use of different features based on color and texture of such turbid
surfaces was conducted. In order to compress the extracted information, Principal Component Analysis (PCA)
was performed and its results were used as inputs to ANN. The whole developed approach was embedded in an
aquatic vehicle, and results and assessments were validated in real environments and different scenarios.
Description
Subject(s)
počítačové vidění, povrch vozidla, analýza hlavních komponent, umělá neuronová síť
Citation
WSCG '2016: short communications proceedings: The 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech RepublicMay 30 - June 3 2016, p. 317-326.