基于形态重建和反向跟踪的粗集料级配视觉检测

doi:10.3969/j.issn.1000-1158.2021.06.04

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Abstract Based on image process method, the detection of particle size for the moving coarse aggregate during the blanking process was studied. A mask-based region of interest (ROI) extraction method combined with the region growth method was introduced to solve the statistical problem of incomplete aggregates at the edge of the image. And a ROI image was gotten in which the aggregate particles had a complete morphology. Then, a statistical method determined the maximum frame sampling interval, ensuring every aggregate counted and image processing efficiency increased. Aiming at solving the problem of aggregates which appeared repeatedly in consecutive images, a reverse tracking algorithm based on touch-type association gate was proposed to recognize the recurring aggregate particles, which avoided the repeated statistics of the same aggregate particles in consecutive images. Finally, the aggregate size distribution was analyzed by using the equivalent ellipse Feret minor axis as the equivalent particle size of aggregate and optimizing the relationship between pixel size and actual size. The experimental results show that the accuracy of recurring particle recognition is 98.08% and the accuracy of aggregate size distribution is 95.59%.

Key words： metrology visual detection grading of coarse aggregate morphological reconstruction reverse tracking ROI extraction method particle size distribution

Received: 19 June 2020 Published: 23 June 2021

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TB96

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	Articles by authors
	CHEN Ze-qi
	FAN Wei-jun
	GUO Bin
	JIANG Wen-song

Cite this article:

CHEN Ze-qi,FAN Wei-jun,GUO Bin, et al. A Visual Detection Method for Particle Size of Moving Coarse Aggregate Based on Morphological Reconstruction and Reverse Tracking[J]. Acta Metrologica Sinica, 2021, 42(6): 710-717.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2021.06.04 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2021/V42/I6/710

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