Obstacle detection algorithms in thermal infrared images for collision avoidance

Adrian Carrio, Srikanth Saripalli, Pascual Campoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Obstacle detection is an essential component in any Sense and Avoid system. Thermal Infrared (TIR) imaging technology can provide enhanced capabilities to current vision-based SAA systems, allowing for operation under extreme illumination conditions, such as direct sun exposure, and during the night. This paper presents a comparison of image processing algorithms for the detection of flying obstacles in TIR images, including both methods based in morphological operations and methods based in the Discrete Haar Wavelet Transform (DHWT). To the author's knowledge, the use of these methods for obstacle detection in TIR images is completely novel. These algorithms have been evaluated on a dataset of more than 5K image pairs, including both ground-based and airborne TIR images. This dataset includes images captured under very different illumination conditions (normal exposure, direct sun exposure and at night) and with various sky conditions (clear and cluttered skies). Conclusions validate these algorithms by presenting measurements in terms of precision and recall for the detection of flying obstacles in several video sequences and a study of the computational cost of the evaluated algorithms.

Original languageEnglish (US)
Title of host publication7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy
PublisherAmerican Helicopter Society International
StatePublished - 2017
Event7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy - Mesa, United States
Duration: Jan 24 2017Jan 26 2017

Other

Other7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy
CountryUnited States
CityMesa
Period1/24/171/26/17

Fingerprint

Collision avoidance
Infrared radiation
Infrared imaging
Sun
Lighting
Discrete wavelet transforms
Image processing
Hot Temperature
Costs

ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Carrio, A., Saripalli, S., & Campoy, P. (2017). Obstacle detection algorithms in thermal infrared images for collision avoidance. In 7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy American Helicopter Society International.

Obstacle detection algorithms in thermal infrared images for collision avoidance. / Carrio, Adrian; Saripalli, Srikanth; Campoy, Pascual.

7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy. American Helicopter Society International, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Carrio, A, Saripalli, S & Campoy, P 2017, Obstacle detection algorithms in thermal infrared images for collision avoidance. in 7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy. American Helicopter Society International, 7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy, Mesa, United States, 1/24/17.
Carrio A, Saripalli S, Campoy P. Obstacle detection algorithms in thermal infrared images for collision avoidance. In 7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy. American Helicopter Society International. 2017
Carrio, Adrian ; Saripalli, Srikanth ; Campoy, Pascual. / Obstacle detection algorithms in thermal infrared images for collision avoidance. 7th AHS Technical Meeting on VTOL Unmanned Aircraft Systems and Autonomy. American Helicopter Society International, 2017.
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