Automatic UAV-based airport pavement inspection using mixed real and virtual scenarios

Pablo Alonso; Jon Ander Iñiguez de Gordoa; Juan Diego Ortega; Sara García; Francisco Javier Iriarte; Marcos Nieto

doi:10.1117/12.2679734

7 June 2023 Automatic UAV-based airport pavement inspection using mixed real and virtual scenarios

Pablo Alonso, Jon Ander Iñiguez de Gordoa, Juan Diego Ortega, Sara García, Francisco Javier Iriarte, Marcos Nieto

Proceedings Volume 12701, Fifteenth International Conference on Machine Vision (ICMV 2022); 1270118 (2023) https://doi.org/10.1117/12.2679734
Event: Fifteenth International Conference on Machine Vision (ICMV 2022), 2022, Rome, Italy

Abstract

Runway and taxiway pavements are exposed to high stress during their projected lifetime, which inevitably leads to a decrease in their condition over time. To make sure airport pavement condition ensure uninterrupted and resilient operations, it is of utmost importance to monitor their condition and conduct regular inspections. UAV-based inspection is recently gaining importance due to its wide range monitoring capabilities and reduced cost.In this work, we propose a vision-based approach to automatically identify pavement distress using images captured by UAVs. The proposed method is based on Deep Learning (DL) to segment defects in the image. The DL architecture leverages the low computational capacities of embedded systems in UAVs by using an optimised implementation of EfficientNet feature extraction and Feature Pyramid Network segmentation. To deal with the lack of annotated data for training we have developed a synthetic dataset generation methodology to extend available distress datasets. We demonstrate that the use of a mixed dataset composed of synthetic and real training images yields better results when testing the training models in real application scenarios.

Citation Download Citation

Pablo Alonso, Jon Ander Iñiguez de Gordoa, Juan Diego Ortega, Sara García, Francisco Javier Iriarte, and Marcos Nieto "Automatic UAV-based airport pavement inspection using mixed real and virtual scenarios", Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 1270118 (7 June 2023); https://doi.org/10.1117/12.2679734

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KEYWORDS

Image segmentation

Data modeling

Inspection

Unmanned aerial vehicles

RGB color model

Cameras

Visualization

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