Real-time construction of sloshing-induced hydrodynamic field based on an intelligent image processing technique integrated with artificial damping model

2021 ◽  
Vol 219 ◽  
pp. 108382
Author(s):  
Yuan Liu ◽  
Jierao Dai ◽  
Chongwei Zhang
2020 ◽  
Vol 13 (2) ◽  
pp. 32
Author(s):  
Hsu Myat Tin Swe ◽  
Hla Myo Tun ◽  
Maung Maung Latt

The paper mainly emphasizes on the control design for attitude and position based on real time color tracking system with image processing technique. The research problem in this study is to observe the high accuracy of the tracking system in image processing areas. The solution for this problem is to control the attitude and position of the object based on real time color tracking system. The objective of this study is to implement the image processing algorithms for autonomous tracking system. The specific objective of this study was fulfilled the experimental studies for contribution of real time color tracking for motion detection system in reality based on this study. This system is used the high performance camera to improve the enactment of tracking of a target and estimation of a motion. An image processing system consists of a light source to illuminate the sense, a sensor system, an interface between the sensor system and the computer. Then, color component analysis is used for color tracking system. MATLAB is competently used for tracking the ball and controlling the attitude and position of the ball.


Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3564
Author(s):  
Thi Thi Zin ◽  
Moe Zet Pwint ◽  
Pann Thinzar Seint ◽  
Shin Thant ◽  
Shuhei Misawa ◽  
...  

Nowadays, for numerous reasons, smart farming systems focus on the use of image processing technologies and 5G communications. In this paper, we propose a tracking system for individual cows using an ear tag visual analysis. By using ear tags, the farmers can track specific data for individual cows such as body condition score, genetic abnormalities, etc. Specifically, a four-digit identification number is used, so that a farm can accommodate up to 9999 cows. In our proposed system, we develop an individual cow tracker to provide effective management with real-time upgrading enforcement. For this purpose, head detection is first carried out to determine the cow’s position in its related camera view. The head detection process incorporates an object detector called You Only Look Once (YOLO) and is then followed by ear tag detection. The steps involved in ear tag recognition are (1) finding the four-digit area, (2) digit segmentation using an image processing technique, and (3) ear tag recognition using a convolutional neural network (CNN) classifier. Finally, a location searching system for an individual cow is established by entering the ID numbers through the application’s user interface. The proposed searching system was confirmed by performing real-time experiments at a feeding station on a farm at Hokkaido prefecture, Japan. In combination with our decision-making process, the proposed system achieved an accuracy of 100% for head detection, and 92.5% for ear tag digit recognition. The results of using our system are very promising in terms of effectiveness.


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