scholarly journals RESEARCH OF THE METHOD OF INCREASING THE OBJECT DETERMINATION ACCURACY ON THE LOW-RESOLUTION VIDEO STREAM

2021 ◽  
Vol 5 (2) ◽  
pp. 91-97
Author(s):  
Валерій Барсов ◽  
Олена Костерна ◽  
Олександр Плахотний
Keyword(s):  
Vision System ◽  
Maximum Error ◽  
Video Stream ◽  
Geometric Object ◽  
Geometric Parameters ◽  
Low Resolution ◽  
Object Parameters ◽  
Python Programming ◽  
Experimental Researches

Study subject. The article proposes and investigates a method for increasing the accuracy of determination of the distance and the obstacle geometric parameters based on object contours determination using a computer vision system that uses low-resolution sensors. The goal is the effectiveness evaluation of the proposed method. Tasks: to conduct experimental researches of the quality indicators of the method of increasing the object contours determination accuracy; evaluate the effectiveness of this method. Used methods: statistical modeling, laboratory scale tests. The obtained results: the analysis of the proposed method efficiency was carried out and the influence of this method on the determination accuracy of the distance and object geometric parameters was evaluated. Conclusions: the considered method made it possible to achieve the increasing the determination accuracy of the distance and geometric object parameters by compensating for image blur using the Lucy-Richardson deconvolution algorithm. The obtained data showed a decrease in the maximum error in determining the distance from 8% to 4% and the error in the geometric object parameters from 7.7% to 5.8%. The implementation of this approach was carried out in the Python programming language.

scholarly journals Development of Non Expensive Technologies for Precise Maneuvering of Completely Autonomous Unmanned Aerial Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 391
Author(s):  
Luca Bigazzi ◽  
Stefano Gherardini ◽  
Giacomo Innocenti ◽  
Michele Basso
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Degrees Of Freedom ◽  
Vision System ◽  
Video Stream ◽  
Measurement Unit ◽  
Absolute Position ◽  
Light Load ◽  
Aerial Vehicles ◽  
Angular Velocities ◽  
Custom Hardware

In this paper, solutions for precise maneuvering of an autonomous small (e.g., 350-class) Unmanned Aerial Vehicles (UAVs) are designed and implemented from smart modifications of non expensive mass market technologies. The considered class of vehicles suffers from light load, and, therefore, only a limited amount of sensors and computing devices can be installed on-board. Then, to make the prototype capable of moving autonomously along a fixed trajectory, a “cyber-pilot”, able on demand to replace the human operator, has been implemented on an embedded control board. This cyber-pilot overrides the commands thanks to a custom hardware signal mixer. The drone is able to localize itself in the environment without ground assistance by using a camera possibly mounted on a 3 Degrees Of Freedom (DOF) gimbal suspension. A computer vision system elaborates the video stream pointing out land markers with known absolute position and orientation. This information is fused with accelerations from a 6-DOF Inertial Measurement Unit (IMU) to generate a “virtual sensor” which provides refined estimates of the pose, the absolute position, the speed and the angular velocities of the drone. Due to the importance of this sensor, several fusion strategies have been investigated. The resulting data are, finally, fed to a control algorithm featuring a number of uncoupled digital PID controllers which work to bring to zero the displacement from the desired trajectory.

Dual-Camera Vision System for Fatigue Monitoring

2012 ◽  
Vol 726 ◽  
pp. 226-232 ◽  
Author(s):  
Tomasz Giesko
Keyword(s):  
Fatigue Fracture ◽  
Vision System ◽  
Specimen Surface ◽  
Fatigue Monitoring ◽  
Computer Unit ◽  
2D Images

The article presents a dual-camera vision system for fatigue monitoring composed of a vision unit, a camera positioning set and a computer unit. Vision modules are mounted onto the 4DOF positioning sets, which allows for an easy determination of the position of the camera in relation to the sample. The application of motorized measurement lenses with changeable configuration, thanks to the alteration of the distance of observation and the vision angle, enables the adaptation of the system to different scales of observation of the fatigue processes in the specimen surface. Automatic focus setting is realised with the use of the implemented algorithm. The software developed allows for the analysis of fatigue fracture for two 2D images or the 3D stereovision image.

scholarly journals AUTOMATIC MAPPING OF GLACIER BASED ON SAR IMAGERY BY BENEFITS OF FREELY OPTICAL AND THERMAL DATA

2015 ◽  
Vol XL-3/W2 ◽  
pp. 47-51
Author(s):  
L. Fang ◽  
L. Hoegner ◽  
U. Stilla
Keyword(s):  
Land Surface ◽  
Low Resolution ◽  
Glacier Surface ◽  
Thermal Data ◽  
Automatic Mapping ◽  
Resources Evaluation ◽  
Sar Imagery ◽  
Normalized Difference Snow Index ◽  
Occurrence Matrix

For many research applications like water resources evaluation, determination of glacier specific changes, and for calculation of the past and future contribution of glaciers to sea-level change, parameters about the size and spatial distribution of glaciers is crucial. In this paper, an automatic method for determination of glacier surface area using single track high resolution TerraSAR-X imagery by benefits of low resolution optical and thermal data is presented. Based on the normalized difference snow index (NDSI) and land surface temperature (LST) map generated from optical and thermal data combined with a surface slope data, a low resolution binary mask was derived used for the supervised classification of glacier using SAR imagery. Then, a set of suitable features is derived from the SAR intensity image, such as the texture information generated based on the gray level co-occurrence matrix (GLCM), and the intensity values. With these features, the glacier surface is discriminated from the background by Random Forests (RF) method.

scholarly journals Technical vision system to ensure the movement of a group of multicopters

2020 ◽  
pp. 13-24
Author(s):  
Yurii Bobkov ◽  
Pavlo Pishchela
Keyword(s):  
Vision System ◽  
Video Stream ◽  
Reference Object ◽  
Maximum Relative Error ◽  
Software Environment ◽  
Technical Vision ◽  
Additional Equipment ◽  
C Programming ◽  
In The Beginning ◽  
Color Depth

The actual task of controlling a group of multicopters performing coordinated actions and are locating at short distances from each other, cannot be performed with the help of a standard on-board autopilot on GPS or GLONASS signals, which give large errors. The solution to this problem is possible due to additional equipment that allows you to set the distance between the multicopters and their relative position. To do this, it is proposed to mark each multicopter with an image label in the form of a standard geometric figure or a geometric body of a given color and size, and to use technical vision system and image recognition algorithms. The structure of the technical vision system for the multicopter was developed and algorithms for image processing and calculation of the change of coordinates of the neighboring multicopter, which are transmitted to the control system to introduce the necessary motion correction, were proposed. The method to identify the reference object in the image of the scene by its color was used in this work. This method is very effective compared to other methods, because it requires only one pass per pixel, which gives a significant advantage in speed during video stream frame processing. RGB color model with a color depth of 24-bit was chosen based on the analysis. Since the lighting during the flight can change, the color is set by the limits of change of the components R, G, B. To determine the distance between multicopters, a very simple but effective method of determination the area of the recognition object (labels on the neighboring multicopter) with next comparation it with the actual value is used. Since the reference object is artificial, its area can be specified with high accuracy. The offset of the center of the object from the center of the frame is used to calculate the other two coordinates. In the beginning, the specific camera instance is calibrated both for a known value of the area of the object and for its displacement along the axes relative to the center of the frame. The technical vision system model in the Simulink software environment of the Matlab system was created to test the proposed algorithms. Based on the simulation results in Simulink, you can generate code in the C programming language for further implementation of the system in real time. A series of studies of the model was conducted using a Logitech C210 webcam with a 0.3 megapixel photo matrix (640x480 resolution). According to the results of the experiment, it was found that the maximum relative error in determining the coordinates of the multicopter did not exceed 6.8 %.

scholarly journals Determination of ASI and THIV parameters based on the results of experimental and numerical research in relation to EU standards

2021 ◽  
Vol 338 ◽  
pp. 01025
Author(s):  
Michał Stopel
Keyword(s):  
Experimental Tests ◽  
Severity Index ◽  
Point Of View ◽  
The Finite Element Method ◽  
Safety Level ◽  
The Road ◽  
Road Sign ◽  
Numerical Research ◽  
Python Programming

Determining the values of ASI (Acceleration Severity Index) and THIV (Theoretical Head Impact Velocity) parameters during tests allows you to assign an appropriate class for a given type of object to determine the safety level and to give the CE marking. The paper presents the methodology for determining these parameters based on the EN 1317-1 and EN 12767 standards. The paper also presents a tool created with the use of the Python programming language, which, based on the results of experimental tests or the results of numerical calculations, allows to determine the ASI and THIV values. The values of key parameters from the point of view of normative tests were calculated based on the results of experimental tests of the road sign supporting mast and numerical analysis carried out for the same case using the Finite Element Method and LS-Dyna software, following the EN 12767 standard.

scholarly journals Kalman filtering for dynamic motion and model estimation

2021 ◽  
Author(s):  
Randal Schumacher.
Keyword(s):  
Kalman Filtering ◽  
Vision System ◽  
Target Position ◽  
Model Estimation ◽  
Mass Center ◽  
Extended Kalman Filtering ◽  
Dynamic Motion ◽  
Filtering Technique ◽  
Time Determination

The fundamental task of a space vision system for rendezvous, capture, and servicing of satellites on-orbit is the real-time determination of the motion of the target vehicle as observed on-board a chaser vehicle. Augmenting the architecture to incorporate the highly regarded Kalman filtering technique can synthesize a system that is more capable, more efficient and more robust. A filter was designed and testing was conducted in an inertial environment and then in a more realistic relative motion orbital rendezvous scenario. The results indicate that a Dynamic Motion Filter based on extended Kalman filtering can provide the vision system routines with excellent initialization leading to faster convergence, reliable pose estimation at slower sampling rates, and the ability to estimate target position, velocity, orientation, angular velocity, and mass center location.

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