Automatic Ship Detection on Multispectral and Thermal Infrared Aerial Images Using MACS-Mar Remote Sensing Platform

Brauchle, Jörg; Bayer, Steven; Berger, Ralf

doi:10.1007/978-3-319-92753-4_30

Cited by 11 publications

(13 citation statements)

References 17 publications

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“…Afterwards, the real-time processing chain was ported to a miniaturized UAV-based camera system. The first phase was successfully accomplished within an aircraft-based experiment in maritime environment, exercised in 2017 over the North Sea off Cuxhaven, Germany [38]. For data downlink, a civil WiFi-based radio link with pointing antennas on both sides was used (see Figure 12a).…”

Section: Resultsmentioning

confidence: 99%

Integrated UAV-Based Real-Time Mapping for Security Applications

Hein

Kraft

Brauchle

et al. 2019

IJGI

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Security applications such as management of natural disasters and man-made incidents crucially depend on the rapid availability of a situation picture of the affected area. UAV-based remote sensing systems may constitute an essential tool for capturing aerial imagery in such scenarios. While several commercial UAV solutions already provide acquisition of high quality photos or real-time video transmission via radio link, generating instant high-resolution aerial maps is still an open challenge. For this purpose, the article presents a real-time processing tool chain, enabling generation of interactive aerial maps during flight. Key element of this tool chain is the combination of the Terrain Aware Image Clipping (TAC) algorithm and 12-bit JPEG compression. As a result, the data size of a common scenery can be reduced to approximately 0.4% of the original size, while preserving full geometric and radiometric resolution. Particular attention was paid to minimize computational costs to reduce hardware requirements. The full workflow was demonstrated using the DLR Modular Airborne Camera System (MACS) operated on a conventional aircraft. In combination with a commercial radio link, the latency between image acquisition and visualization in the ground station was about 2 s. In addition, the integration of a miniaturized version of the camera system into a small fixed-wing UAV is presented. It is shown that the described workflow is efficient enough to instantly generate image maps even on small UAV hardware. Using a radio link, these maps can be broadcasted to on-site operation centers and are immediately available to the end-users.

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Section: Resultsmentioning

confidence: 99%

Integrated UAV-Based Real-Time Mapping for Security Applications

Hein

Kraft

Brauchle

et al. 2019

IJGI

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“…12). Using a thermal IR image, the correctness will significantly increase as shown in preliminary [27] and following [38] work.…”

Section: Object Detection Analysismentioning

confidence: 93%

“…A second campaign was examined in August 2017 adding thermal imagery. The paper is accepted and to be released in near future [38]. Next steps should be acquiring a greater database to make the algorithm more robust against image errors and thus avoiding detection of seemingly very small objects.…”

Section: Future Workmentioning

confidence: 99%

MACS-Mar: a real-time remote sensing system for maritime security applications

et al. 2018

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The modular aerial camera system (MACS) is a development platform for optical remote sensing concepts, algorithms and special environments. For real-time services for maritime security (EMSec joint project), a new multi-sensor configuration MACS-Mar was realized. It consists of four co-aligned sensor heads in the visible RGB, near infrared (NIR, 700-950 nm), hyperspectral (HS, 450-900 nm) and thermal infrared (TIR, 7.5-14 µm) spectral range, a mid-cost navigation system, a processing unit and two data links. On-board image projection, cropping of redundant data and compression enable the instant generation of direct-georeferenced high-resolution image mosaics, automatic object detection, vectorization and annotation of floating objects on the water surface. The results were transmitted over a distance up to 50 km in real-time via narrow and broadband data links and were visualized in a maritime situation awareness system. For the automatic onboard detection of floating objects, a segmentation and classification workflow based on RGB, IR and TIR information was developed and tested. The completeness of the object detection in the experiment resulted in 95%, the correctness in 53%. Mostly, bright backwash of ships lead to an overestimation of the number of objects, further refinement using water homogeneity in the TIR, as implemented in the workflow, couldn't be carried out due to problems with the TIR sensor, else distinctly better results could have been expected. The absolute positional accuracy of the projected real-time imagery resulted in 2 m without postprocessing of images or navigation data, the relative measurement accuracy of distances is in the range of the image resolution, which is about 12 cm for RGB imagery in the EMSec experiment.

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“…Images were acquired using the instrument MACS (Modular Aerial Camera System), cf. [36,37]. A picture of the MACS camera system can be found on figure 5.…”

Section: Macs and Image Datamentioning

confidence: 99%

AMARO—An On-Board Ship Detection and Real-Time Information System

Willburger

Schwenk

Brauchle

2020

Sensors

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The monitoring of worldwide ship traffic is a field of high topicality. Activities like piracy, ocean dumping, and refugee transportation are in the news every day. The detection of ships in remotely sensed data from airplanes, drones, or spacecraft contributes to maritime situational awareness. However, the crucial factor is the up-to-dateness of the extracted information. With ground-based processing, the time between image acquisition and delivery of the extracted product data is in the range of several hours, mainly due to the time consumed by storing and transmission of the large image data. By processing and analyzing them on-board and transmitting the product data directly as ship position, heading, and velocity, the delay can be shortened to some minutes. Real-time connections via satellite telecommunication services allow small packets of information to be sent directly to the user without significant delay. The AMARO (Autonomous Real-Time Detection of Moving Maritime Objects) project at DLR is a feasibility study of an on-board ship detection system involving on-board processing and real-time communication. The operation of a prototype system was successfully demonstrated on an airborne platform in spring 2018. The on-ground user could be informed about detected vessels within minutes after sighting without a direct communication link. In this article, the scope, aim, and design of the AMARO system are described, and the results of the flight experiment are presented in detail.Sensors 2020, 20, 1324 2 of 23 collision avoidance. Ships send out their identification, position, course, speed, and several other traffic-related data. This data is then received by other ships and ground stations in close range. Nowadays, to be able to track ships globally in real-time, satellites are also used to receive AIS data [7]. However, based on AIS data only, the detection of illegal activities like water pollution, illegal fishing, or smuggling is limited.To improve maritime domain awareness, Earth observation (EO) satellite data is a valuable source of information. Great efforts are made in researching the potential of vessel detection in optical and radar satellite images [8][9][10]. However, in most cases, these images are analyzed long after the data have been acquired [11]. To tackle this bottleneck, there is also promising progress in establishing near-real-time services on the ground, which today can provide information in, at best, the range of 15 min, measured from on-ground data reception [12,13]. However, the most significant time delay occurs between data acquisition on-board and data reception on-ground, since image data are comparatively huge and their downlink requires a direct contact to a ground station. This delay can amount to hours or even days [14].A second drawback of EO satellites for time-critical applications is their inability to continuously monitor a defined region of interest. Satellites with a reasonable spatial resolution for ship detection orbit in LEO (low Earth orbit) with speeds of a...

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Automatic Ship Detection on Multispectral and Thermal Infrared Aerial Images Using MACS-Mar Remote Sensing Platform

Cited by 11 publications

References 17 publications

Integrated UAV-Based Real-Time Mapping for Security Applications

Integrated UAV-Based Real-Time Mapping for Security Applications

MACS-Mar: a real-time remote sensing system for maritime security applications

AMARO—An On-Board Ship Detection and Real-Time Information System

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