Technical vision system for quality control of objects of the ball-shaped form when sorting on the conveyor

A functional diagram of a robotic complex mock-up for rejecting ball-shaped objects transported on a roller conveyor is presented. The software of the complex is designed to detect an object on the conveyor and determine its coordinates. To detect objects of control, their images obtained in the vis...

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Published in:Journal of physics. Conference series Vol. 1546; no. 1; pp. 12001 - 12007
Main Authors: Balabanov, P V, Divin, A G, Belyaev, P S, Trapeznikov, E V, Egorov, A S, Zaharov, Y A, Yudaev, V A, Don-Uni, Nseno-Pemby
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.05.2020
Subjects:
Algorithms
Gravity conveyors
Object recognition
Quality control
Software
Spectrograms
Surface defects
Vision systems
ISSN:1742-6588, 1742-6596
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Abstract A functional diagram of a robotic complex mock-up for rejecting ball-shaped objects transported on a roller conveyor is presented. The software of the complex is designed to detect an object on the conveyor and determine its coordinates. To detect objects of control, their images obtained in the visible range of the optical spectrum and Viola-Jones object detection algorithms are employed. The developed software is based on a trained cascade classifier, the optimal settings of which are determined. To detect surface defects of objects, their spectrograms obtained in the range of 400... 1000 nm are used. The presented results can be applied to the process automation of sorting fruits and vegetables and other ball-shaped objects.
AbstractList A functional diagram of a robotic complex mock-up for rejecting ball-shaped objects transported on a roller conveyor is presented. The software of the complex is designed to detect an object on the conveyor and determine its coordinates. To detect objects of control, their images obtained in the visible range of the optical spectrum and Viola-Jones object detection algorithms are employed. The developed software is based on a trained cascade classifier, the optimal settings of which are determined. To detect surface defects of objects, their spectrograms obtained in the range of 400... 1000 nm are used. The presented results can be applied to the process automation of sorting fruits and vegetables and other ball-shaped objects.
Author Divin, A G
Balabanov, P V
Yudaev, V A
Belyaev, P S
Trapeznikov, E V
Egorov, A S
Don-Uni, Nseno-Pemby
Zaharov, Y A
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SubjectTerms Algorithms
Gravity conveyors
Object recognition
Quality control
Software
Spectrograms
Surface defects
Vision systems
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