Toward UAV based compact thermal infrared hyperspectral imaging solution for real-time gas detection identification and quantification (Conference Presentation)

2019 ◽  
Author(s):  
Stephane Boubanga Tombet ◽  
Frédérick Marcotte ◽  
Éric Guyot ◽  
Martin Chamberland ◽  
Vincent Farley
Keyword(s):  
Real Time ◽  
Hyperspectral Imaging ◽  
Thermal Infrared ◽  
Gas Detection ◽  
Identification And Quantification

scholarly journals Detection, Identification, and Quantification of SF6 Point-Source Emissions Using Hyper-Cam LW Airborne Platform

2021 ◽  
Vol 25 (3) ◽  
pp. 37-41
Author(s):  
Mariusz Kastek ◽  
Krzysztof Firmanty ◽  
Benjamin Saute ◽  
Philippe Gagnon ◽  
Martin Lariviere-Bastien ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Hyperspectral Imaging ◽  
Hyperspectral Data ◽  
Gas Detection ◽  
Gas Release ◽  
Imaging Data ◽  
Regulatory Guidelines ◽  
Quantification Analysis ◽  
Processing Algorithms ◽  
Identification And Quantification

Detection, identification, and quantification of greenhouse gases is essential to ensure compliance with regulatory guidelines and mitigate damage associated with anthropogenic climate change. Passive infrared hyperspectral imaging technology is among the solutions that can detect, identify and quantify multiple greenhouse gases simultaneously. The Telops Hyper-Cam Airborne Platform is an established system for aerial thermal infrared hyperspectral measurements for gas survey applications. In support of the Hypercam, is developing a suite of hyperspectral imaging data processing algorithms that allow for gas detection, identification, and quantification in real-time. In the Fall of 2020, the Hyper-Cam-LW Airborne platform was flown above a validated SF6 gas release system to collect hyperspectral data for gas quantification analysis. This measurement campaign was performed to document performance of the Hyper-Cam gas quantification capabilities against known quantities of released gas.

Real time airborne gas detection using thermal hyperspectral imaging (Conference Presentation)

2018 ◽  
Author(s):  
Stephane Boubanga Tombet ◽  
Alexandrine Huot ◽  
Éric Guyot ◽  
Vincent Farley ◽  
Frédérick Marcotte ◽  
...  
Keyword(s):  
Real Time ◽  
Hyperspectral Imaging ◽  
Gas Detection

scholarly journals Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Hyperspectral Imaging ◽  
High Speed ◽  
Detection System ◽  
Imaging Techniques ◽  
Foreign Object ◽  
Subtraction Method ◽  
Foreign Objects ◽  
Time Operation

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

Direct imaging of shale gas leaks using passive thermal infrared hyperspectral imaging

2017 ◽  
Author(s):  
Marc-Andre Gagnon ◽  
Pierre Tremblay ◽  
Simon Savary ◽  
Vince Morton ◽  
Vincent Farley ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Shale Gas ◽  
Thermal Infrared ◽  
Direct Imaging ◽  
Gas Leaks
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