Drone Based Aerial Imaging For Post-Disaster ReconnaissanceThéau Héral1, William Greenwood2, Dimitrios Zekkos2, PhD, PE and Jerome Lynch2, PhD

1Department of Aerospace Engineering • 2Department of Civil and Environmental Engineering • University of Michigan • Ann Arbor, MIEmail: theau@umich.edu • wwgreen@umich.edu • zekkos@umich.edu

References1. Alaska Dispatch News, (4/19/2015), http://www.adn.com/2. The Atlantic, (4/19/2015), http://www.theatlantic.com/magazine/archive/2010/12/the-drone-

wars/308304/3. Baiocchi, V., Dominici, D., & Mormile, M. (2013). UAV application in post-seismic environment. Int. Arch.

Photogramm. Remote Sens. Spatial Inf. Sci., XL-1 W, 2, 21-25.4. Cinehawk, (4/19/2015), http://cinehawk.co.uk/blog/drone-filming-uk/5. Direct Relief, (4/19/2015), https://www.directrelief.org/2013/12/civil-drones-improve-humanitarian-

response-philippines/6. DJI, (4/19/2015), http://www.dji.com/7. Factor, (4/19/2015), http://factor-tech.com/drones/7363-delivery-drones-closer-to-reality-with-self-

monitoring-quadcopters/8. Huang Y B, Thomson S J, Hoffmann W C, Lan Y B, Fritz B K. Development and prospect of unmanned

aerial vehicle technologies for agricultural production management. Int J Agric & Biol Eng,2013;6(3):1-10.9. MatLab Documentation, (4/19/2015), http://www.mathworks.com/help/matlab/10. Remondino, F., Barazzetti, L., Nex, F., Scaioni, M., & Sarazzi, D. (2011). UAV photogrammetry for mapping

and 3d modeling–current status and future perspectives. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(1), C22.

11. Tweaktown, (4/19/2015), http://www.tweaktown.com/news/42572/faa-issues-drone-permits-real-estate- agriculture-commercial-use/index.html

ConclusionsThere is a wide array of imaging and computer vision applications for UAVswith the ability to impact many industries such public safety, agriculture, andengineering. One such application is post-disaster reconnaissance andinfrastructure assessment. Before images and video can be utilized, post-processing for lens corrections is required. A MatLab program has beenwritten for automatically correcting radial distortion in photos and videostaken by a Phantom 2 Vision+ UAV. The code is flexible enough to be adaptedfor other cameras and UAVs. The lens correction has been integrated with asimple crack detection algorithm and will be incorporated with detection ofother features related to geotechnical engineering.

AbstractImmediately following natural disasters, such as earthquakes, reconnaissancestudies are performed to collect data and observe damage to infrastructureand geotechnical systems. However, access to sites is often limited due tosafety considerations, difficulty and time. An Unmanned Autonomous AerialVehicle (UAAV) capable of gaining access to these areas could solve manyproblems and lead to more efficient post-disaster reconnaissance. A UAAVsite reconnaissance and characterization platform is being developed. Amongthe many data collection features, the UAAV will collect photos and videosused to identify damage and features of interest. Commercial UnmannedAerial Vehicles (UAVs), for performing preliminary field testing, werecompared. The DJI Phantom 2 Vision + was selected after an investigation ofthe UAVs most commonly used with image processing techniques. Photos andvideos recorded by the Phantom are used as the basis for calibrating imageprocessing methods for identifying geotechnical features of interest. Beforethese aerial images and videos can be used for this purpose, significant post-processing is required. A MatLab program was developed to automaticallydetect photos and videos and batch process them to apply the necessarycorrections. A correction for lens distortion is applied to remove the barreleffect (also known as fisheye effect) caused by the Phantom camera lens.Once the photos are corrected, they were used for automated crackdetection.

AcknowledgementsThe authors would like to acknowledge funding from Rackham GraduateSchool of the University of Michigan – Ann Arbor through a RackhamGraduate Student Research Grant. The authors would like to thank BobSpence and Jan Pantolin for efforts in constructing the indoor flight facility.The graduate student is further funded by NSF grant award #1362975.

Image Processing

Lens Correction

• Correct radial lens distortion (“fisheye”)• Inputs: Intrinsic Matrix and radial distortion

coefficients specific to the camera

Crack detection

• Performed on grayscale images (ignoring color)• 2D Gaussian filter is applied to the image• The low-pass filter smooths the image• Possible cracks are traced by detecting gradients above a specified

threshold

Applications of Drone Technology

Agriculture

• Health monitoring, crop duster,… Huang et al. (2013)

Atmospheric Measures

• Pollution, meteorology,…

Cinematography and Photography

• Aerial views of events, movies,…

Delivery

• Home delivery, medical supply delivery,…

Disaster Assessment

• Earthquakes, tornado, floods, wildfire, search and rescue,… Baiocchi et al. (2013)

Mapping

• Remote mapping, 3D mapping, archeology… Remondino et al.(2011)

Disaster Reconnaissance

Objective

Development of a UAAV site reconnaissance and characterization platform:• Photo and video recording;• LiDAR scans to collect point clouds of surface deformations; • Wireless sensor deployment of set predetermined geophone arrays,• Perform in situ shear wave velocity measurements.

Method

The research focused first on understanding the state-of-the-art practices andapplications of imaging drones with a literature review. Once the DJI Phantom2 Vision+ was chosen, the images/videos acquisition was conducted byoperating the drone in an indoor cage. MatLab codes for post-processing thecollected images were developed & incorporate feature detection algorithms.

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DJI Phantom 2 Vision + Specifications

Aircraft Specifications

Battery Autonomy 20-25 minCommunication Distance (open area) 500-700mHover Accuracy (Ready to Fly) Vertical: 0.8m; Horizontal: 2.5mOnscreen Real-Time Flight Parameters Photography and Waypoints3-axis High Performance Gimbal Control Accuracy: ±0.03°

FC 200 Camera

Operating Environment Temperature 0℃-40℃Sensor size 1/2.3"Effective Pixels 14 MegapixelsResolution 4384×3288HD Recording 1080p30 & 720pRecording Field Of View (FOV) 110° / 85°

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Lens CorrectionProblem: “Fisheye” lens causes barrel distortion

Batch Process

User input: Save video frames or not

and at what interval?

Correct images

Save frames from video

Save images & EXIF data

Start End

Input Images or

videos

Correct frame by frame and saves in a new corrected video

Collect photos and images

Save frames or

not

Uncorrected Corrected

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