International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Dec. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 140
Paper Published : 1764
No. of Authors : 4906
  Journal Paper


Paper Title :
Building A Quad Robot for Image Processing and its Controller to Capture Images from the Environment

Author :Turaj Arminpour, Mehrdad Mansouri, Mahsa Shoshtari

Article Citation :Turaj Arminpour ,Mehrdad Mansouri ,Mahsa Shoshtari , (2024 ) " Building A Quad Robot for Image Processing and its Controller to Capture Images from the Environment " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 19-26, Volume-12,Issue-3

Abstract : Due to its special design compared to other helicopters, Chaharmalkh or the same four-propeller helicopter has a more stable flight, which makes it suitable for surveillance and aerial photography, especially in UAV research (unmanned aerial vehicle for gathering information and Taking pictures ) has been used a lot in recent years. Today, four-propeller helicopters are used in various conditions, and in many cases, they are used as a robot with direct user intervention, as a control element in the control loop. Using a human force to control these robots, in addition to the overhead cost that it entails, is not desirable in many circumstances. In times when the robot is used to monitor city traffic, which requires guiding the robot behind buildings, and if there are blind spots, there will be a possibility of losing control of the robot. The purpose of this article is to build a quadcopter with a controller to process the image on the video sent by the quadcopter. Image processing is done by CNN algorithm or convolutional neural network with deep learning and by opencv library. The results implemented by the opencv library show that the designed system performs facial recognition with an accuracy of over 90%. In the system database for image processing, we have used two data samples including about 6,000 human body images and 5,000 non-human body images collected for the purpose of this article. Keywords - Opencv, Image Processing, Deep Learning, Quadcopter, Controller, Convolutional Neural Network

Type : Research paper

Published : Volume-12,Issue-3


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