Target detection and recognition algorithm for moving UAV based on machine vision

To solve the shortcomings that current robot vision system accuracy is instable, unit operation time is overlong and automatic compensation function is lacked, this paper proposes robot vision system based on trinocular vision from the perspective of system hardware structure improvement and softwar...

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Vydáno v:Cluster computing Ročník 22; číslo Suppl 2; s. 4263 - 4269
Hlavní autor: Jun, Mao
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.03.2019
Springer Nature B.V
Témata:
Accuracy
Algorithms
Automation
Calibration
Cameras
Computer Communication Networks
Computer Science
Coordinates
Machine vision
Mean square errors
Operating Systems
Processor Architectures
Robots
Software
Target detection
Vision systems
The minimum mean square error matching
Logic communication
Trinocular vision
Region-of-interest
Robot
Nine-point calibration
ISSN:1386-7857, 1573-7543
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Shrnutí:To solve the shortcomings that current robot vision system accuracy is instable, unit operation time is overlong and automatic compensation function is lacked, this paper proposes robot vision system based on trinocular vision from the perspective of system hardware structure improvement and software algorithm optimization. Firstly, logic communication channel among PLC sensor, robot and vision PC shall be established, to realize real-time acquisition and processing of operation condition of material. Then design nine-point calibration method according to scaling, rotating and translation parameters between robot and vision coordinate system, and calibrate three industrial cameras to realize accurate binding of image pixel coordinate and robot world coordinate. Finally, choose region-of-interest, optimize the minimum mean square error matching algorithm and realize balance of system accuracy and speed according to project standard of product. Experimental test result shows that compared with current robot vision system, system in this paper has higher vision accuracy and operation efficiency.
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ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-018-1857-0