scholarly journals Obstacle detection technique to solve poor texture appearance of the obstacle by categorising image's region using cues from expansion of feature points for small UAV

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Syariful Syafiq Shamsudin ◽  
Muhammad Faiz Ramli
Keyword(s):  
Obstacle Detection ◽  
Detection Technique ◽  
Feature Points ◽  
Small Uav

Obstacle detection technique using multi sensor integration for small unmanned aerial vehicle

2017 ◽  
Vol 8 (2) ◽  
pp. 441 ◽  
Author(s):  
Muhammad Faiz Bin Ramli ◽  
Syariful Syafiq Shamsudin ◽  
Ari Legowo
Keyword(s):  
Indoor Environment ◽  
Detection System ◽  
Obstacle Detection ◽  
Sensor Integration ◽  
Feature Points ◽  
Advantages And Disadvantages ◽  
System A ◽  
Small Uav ◽  
Image Capturing ◽  
Aerial Vehicle

<p class="Abstract">Achieving a robust obstacle detection system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle sizes estimation by searching the connecting feature points in the image frame. Finally, safe avoidance path for UAV is determined through the exterior feature points from the estimated width of the obstacle. The proposed method was evaluated by conducting experiments in real time with indoor environment. In the experiment conducted, we successfully detect and determine a safe avoidance path for the UAV on 6 different sizes and textures of the obstacles including textureless obstacles.</p>

Evaluation of an obstacle detection technique based on stereovision

1993 ◽  
Author(s):  
Serge De Paoli ◽  
Renaud Zigmann ◽  
Thomas Skordas ◽  
H. H. Soudain
Keyword(s):  
Obstacle Detection ◽  
Detection Technique

scholarly journals Sudden Obstacle Appearance Detection by Analyzing Flow Field Vector for Small-Sized UAV

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Muhammad Faiz Ramli ◽  
◽  
Syariful Syafiq Shamsudin ◽  
Mohd Fauzi Yaakub ◽  
◽  
...  
Keyword(s):  
Flow Field ◽  
Detection System ◽  
Wide Spectrum ◽  
Field Vector ◽  
Obstacle Detection ◽  
Physical Size ◽  
High Dependency ◽  
Small Uav ◽  
Aerial Vehicle ◽  
Work Integration

Achieving a reliable obstacle detection and avoidance system that can provide an effective safe avoidance path for small unmanned aerial vehicle (UAV) is very challenging due to its physical size and weight constraints. Prior works tend to employ the vision based-sensor as the main detection sensor but resulting to high dependency on texture appearance while not having a distance sensing capabilities. The previous system only focused on the detection of the static frontal obstacle without observing the environment which may have moving obstacles. On the other hand, most of the wide spectrum range sensors are heavy and expensive hence not suitable for small UAV. In this work, integration of different based sensors was proposed for a small UAV in detecting unpredictable obstacle appearance situation. The detection of the obstacle is accomplished by analysing the flow field vectors in the image frames sequence. The proposed system was evaluated by conducting the experiments in a real environment which consisted of different configuration of the obstacles. The results from the experiment show that the success rate for detecting unpredictable obstacle appearance is high which is 70% and above. Even though some of the introduced obstacles are considered to have poor texture appearances on their surface, the proposed obstacle detection system was still able to detect the correct appearance movement of the obstacles by detecting the edges.

Face Detection With Face Mask for COVID-19 Pandemic Using Neural Networks

2022 ◽  
pp. 210-223
Author(s):  
Nitish Devendra Warbhe ◽  
Rutuja Rajendra Patil ◽  
Tarun Rajesh Shrivastava ◽  
Nutan V. Bansode
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Face Detection ◽  
Face Mask ◽  
Detection Technique ◽  
Facial Features ◽  
Feature Points ◽  
The People ◽  
Biometric Systems ◽  
The Face

The COVID-19 virus can be spread through contact and contaminated surfaces; therefore, typical biometric systems like password and fingerprint are unsafe. Face recognition solutions are safer without any need of touching any device. During the COVID-19 situation as all of the people are advised to wear masks on their faces, the existing face detection technique is not able to identify the person with face occlusion. The fraudsters and thieves take advantage of this scenario and misuse the face mask, favoring them to be able to steal and commit various crimes without being identified. Face recognition methods fail to detect or recognize the face as half of the face is masked and the features are suppressed. Face recognition requires the visibility of major facial features for face normalization, orientation correction, and recognition. Thus, the chapter focuses on the facial recognition based on the feature points surrounding the eye region rather than taking the whole face as a parameter.

Clinical Application and Results of the Assessment of Coronary Blood Flow by the Regional Precordial Xenon Residue Detection Technique

1978 ◽  
Vol 17 (04) ◽  
pp. 161-171
Author(s):  
H.-J. Engel ◽  
H. Hundeshagen ◽  
P. R. Lichtlen
Keyword(s):  
Wall Motion ◽  
High Flow ◽  
Detection Technique ◽  
Fatty Tissue ◽  
Technical Aspects ◽  
Residue Detection ◽  
High Affinity ◽  
Artery Disease ◽  
The Right ◽  
Drug Interventions

Methodological and technical aspects as well as application and results of the precordial Xenon-residue-detection technique are critically reviewed. The results concern mainly normal flow in various regions of the heart esp. in the free wall of the right and left ventricle, poststenotic flow in patients with coronary artery disease in relation to the degree of proximal nar-rowings as well as wall motion of the corresponding LV segment, bypassgraft flow and flow after drug interventions esp. nitrates, betablockers, the calcium-antagonist Nifedipine and the coronary dilator Dipyridamole. In spite of its serious limitations (high affinity of Xenon for fatty tissue, geometrical problems in the assessment of flow and its relation to anatomy, gas exchange in situations of high flow etc.), the technique is found to be a usefull investigatory tool. Due to its technical display and the related high costs routine application is, however, prohibitive.

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