Automated Image Processing Workflow for Unmanned Aerial Vehicles

Author(s):  
Samuel Oswald ◽  
Dries Raymaekers ◽  
Wouter Dierckx ◽  
Dominique De Munck ◽  
Stephen Kempenaers ◽  
...  
2020 ◽  
Vol 161 ◽  
pp. 01087 ◽  
Author(s):  
Marina Vasileva ◽  
Ilyas Ismagilov ◽  
Alexander Gerasimov

The paper contains results of analytic research of unmanned aerial vehicles using in agriculture. The main problems arising in the creation and subsequent large volumes of high-resolution images real time transfer in unmanned aerial vehicles are highlighted. The Automated image processing and transfer system using new methods of information compression on unmanned aerial vehicles board is proposed. The paper considers the issues of consider the problems of constructing new orderings of Walsh functions and constructing fast compression algorithms in synthesized systems of discrete Walsh functions. For processing and subsequent transmission of information from UAVs recommended to use the fast DWT procedure, it allows for a hardware implementation capable of the real-time conversion performing due to its simplicity. The introduction of the proposed solutions for UAVs in agriculture allows to increase accurasy of electronic cartographic material, to keep electronic records of agricultural operations, to carry out operational monitoring of the crops state and to respond quickly for violations and deviations, to predict crop yields and plan their activities for short-term and long-term prospects.


2019 ◽  
Vol 20 (1-2) ◽  
pp. 265-271 ◽  
Author(s):  
Grzegorz Jaromi ◽  
Damian Kordos ◽  
Tomasz Rogalski ◽  
Paweł Rzucidło ◽  
Piotr Szczerba

The work discusses selected elements of research and practical tests of the vision anti-collision system, designed for ultralight and light aircraft and unmanned aerial vehicles. At the outset, current formal requirements related to the necessity of installing anti-collision systems on aircraft are presented. The concept of IDAAS (Intruder Detection And collision Avoidance System for light aircraft) and the structure of algorithms related to image processing were presented. The main part of the work is to discuss the selected scenarios implemented during the research.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Moisés Lodeiro-Santiago ◽  
Pino Caballero-Gil ◽  
Ricardo Aguasca-Colomo ◽  
Cándido Caballero-Gil

This work presents a system to detect small boats (pateras) to help tackle the problem of this type of perilous immigration. The proposal makes extensive use of emerging technologies like Unmanned Aerial Vehicles (UAV) combined with a top-performing algorithm from the field of artificial intelligence known as Deep Learning through Convolutional Neural Networks. The use of this algorithm improves current detection systems based on image processing through the application of filters thanks to the fact that the network learns to distinguish the aforementioned objects through patterns without depending on where they are located. The main result of the proposal has been a classifier that works in real time, allowing the detection of pateras and people (who may need to be rescued), kilometres away from the coast. This could be very useful for Search and Rescue teams in order to plan a rescue before an emergency occurs. Given the high sensitivity of the managed information, the proposed system includes cryptographic protocols to protect the security of communications.


2017 ◽  
Vol 3 (1) ◽  
pp. 4 ◽  
Author(s):  
Esteban Cano ◽  
Ryan Horton ◽  
Chase Liljegren ◽  
Duke Bulanon

2014 ◽  
Vol 1003 ◽  
pp. 216-220 ◽  
Author(s):  
Qi Li ◽  
Yu Yang ◽  
Zhong Ke Li ◽  
Jing Lu

According to the unmanned aerial vehicles real-time video image acquiring and target detection requirements, an image processing system was designed based on FPGA and TVP5150A decoder, and the video decoding hardware and software was also designed to meet the demands of unmanned aerial vehicles. An I2C controller was realized to assure the implementation of video decoding process in accordance with the requirements, and an image processing algorithm and applied to the image recognition process. Both of these were completed in FPGA using verilog HDL language. The correction of this image processing system was verified through real-time experiments.


2020 ◽  
Vol 30 (2) ◽  
pp. 69-79
Author(s):  
A. A. Makarenko ◽  
L. A. Vinokurov

The article states the method of autofocusing of the optoelectronic image, based on digital image processing. Some systems of autofocusing which can be used in optoelectronic equipment of unmanned aerial vehicles are considered. The method developed by authors and the program algorithm implementing it are similar to the rules of functioning of an element of the human visual system which executes an estimation of a spectrum of spatial frequencies for the realization of focusing of the image of objects which are of interest or danger and are on different distance from the observer. The best focusing is defined on the greatest width of a spectrum of spatial frequencies of the object. Such estimation allows focusing the necessary object on the observable image even in the absence of binocular vision. The method is based on the numerical analysis of a two-dimensional amplitude spectrum of the image. Results of operation of the stated method which confirm its efficiency are presented.


2020 ◽  
Vol 117 ◽  
pp. 104813
Author(s):  
D. Ribeiro ◽  
R. Santos ◽  
A. Shibasaki ◽  
P. Montenegro ◽  
H. Carvalho ◽  
...  

Nowadays, quadcopters are commonly used. Quadcopters are unmanned aerial vehicles with four propellers to provide lift to fly and hover above ground. Quadcopter nowadays is a very common commercial item in everyday life. Some quadcopters are designed to do 3D or 2D mapping of a certain area or to take videos or just for entertainment purposes. Quadcopter is a very versatile item and is able to change into anything for example a quadcopter can also be used for security purposes to decrease the crime rate of our country. The objective of this study is to design and develop a quadcopter with image processing system to have the ability to measure the distance of a human from the drone itself. The quadcopter is designed to be small in size and have a mini computer like Raspberry Pi on top of it to compute the algorithm to calculate the distance of the human by using image processing technique through the camera which is setup on the drone. Human detecting algorithm YOLO and software Open CV is chosen to detect human and calculate the distance from the quadcopter. The results show that the system is quite limited by the capabilities of the hardware. The system shows an accuracy of more than 90 percent when the human is standing within a certain range. Both the accuracy of the distance sensing and human recognizing system is affected by the limitation of the hardware.


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