An Embedded System for Aerial Image Processing from Unmanned Aerial Vehicles

2015 ◽  
Author(s):  
Jonas Fernandes da Silva ◽  
Alisson V. Brito ◽  
Jose Antonio Gomes De Lima ◽  
Helder Nogueira De Moura
Keyword(s):  
Image Processing ◽  
Embedded System ◽  
Unmanned Aerial Vehicles ◽  
Aerial Image ◽  
Aerial Vehicles

scholarly journals The development of modern automated image processing and transfer systems for agriculture unmanned aerial vehicles

2020 ◽  
Vol 161 ◽  
pp. 01087 ◽  
Author(s):  
Marina Vasileva ◽  
Ilyas Ismagilov ◽  
Alexander Gerasimov
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Crop Yields ◽  
Walsh Functions ◽  
Aerial Vehicles ◽  
Transmission Of Information ◽  
High Resolution Images ◽  
Automated Image Processing

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.

scholarly journals Selected elements of visual inspection of the collision avoidance system for light and unmanned aircraft

2019 ◽  
Vol 20 (1-2) ◽  
pp. 265-271 ◽  
Author(s):  
Grzegorz Jaromi ◽  
Damian Kordos ◽  
Tomasz Rogalski ◽  
Paweł Rzucidło ◽  
Piotr Szczerba
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Main Part ◽  
Visual Inspection ◽  
Unmanned Aircraft ◽  
Collision System ◽  
Aerial Vehicles ◽  
Collision Avoidance System ◽  
Formal Requirements

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.

scholarly journals Secure UAV-Based System to Detect Small Boats Using Neural Networks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Moisés Lodeiro-Santiago ◽  
Pino Caballero-Gil ◽  
Ricardo Aguasca-Colomo ◽  
Cándido Caballero-Gil
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Image Processing ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
High Sensitivity ◽  
Search And Rescue ◽  
Detection Systems ◽  
Aerial Vehicles ◽  
Current Detection

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.

Automated Image Processing Workflow for Unmanned Aerial Vehicles

2021 ◽  
Author(s):  
Samuel Oswald ◽  
Dries Raymaekers ◽  
Wouter Dierckx ◽  
Dominique De Munck ◽  
Stephen Kempenaers ◽  
...  
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
Automated Image Processing

Aerial Image Stitching Algorithm for Unmanned Aerial Vehicles Based on Improved ORB and PROSAC

2019 ◽  
Vol 56 (23) ◽  
pp. 231003
Author(s):  
李振宇 Li Zhenyu ◽  
田源 Tian Yuan ◽  
陈方杰 Chen Fangjie ◽  
韩军 Han Jun
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Aerial Image ◽  
Image Stitching ◽  
Aerial Vehicles

scholarly journals Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing

2017 ◽  
Vol 3 (1) ◽  
pp. 4 ◽  
Author(s):  
Esteban Cano ◽  
Ryan Horton ◽  
Chase Liljegren ◽  
Duke Bulanon
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles

Design of a New Image Processing System Based on FPGA

2014 ◽  
Vol 1003 ◽  
pp. 216-220 ◽  
Author(s):  
Qi Li ◽  
Yu Yang ◽  
Zhong Ke Li ◽  
Jing Lu
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Target Detection ◽  
Processing System ◽  
Image Processing Algorithm ◽  
Verilog Hdl ◽  
Video Decoding ◽  
Image Processing System ◽  
Aerial Vehicles

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.

An Automatic Robust Image Registration Algorithm for Aerial Mapping

2015 ◽  
Vol 15 (02) ◽  
pp. 1540002 ◽  
Author(s):  
Mohammad Saleh Javadi ◽  
Zulaikha Kadim ◽  
Hon Hock Woon ◽  
Khairunnisa Mohamed Johari ◽  
Norshuhada Samudin
Keyword(s):  
Image Registration ◽  
Unmanned Aerial Vehicles ◽  
Aerial Photograph ◽  
Satellite Images ◽  
Aerial Image ◽  
Registration Algorithm ◽  
Aerial Vehicles ◽  
Image Registration Algorithm ◽  
Aerial Mapping ◽  
Robust Image

Aerial mapping is attracting more attention due to the development in unmanned aerial vehicles (UAVs) and their availability and also vast applications that require a wide aerial photograph of a region in a specific time. The cross-modality as well as translation, rotation, scale change and illumination are the main challenges in aerial image registration. This paper concentrates on an algorithm for aerial image registration to overcome the aforementioned issues. The proposed method is able to sample automatically and align the sensed images to form the final map. The results are compared with satellite images that shows a reasonable performance with geometrically correct registration.

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