基于Mask R-CNN算法的尾矿库干滩长度视频测量研究

doi:10.3969/j.issn.1000-1158.2020.12.04

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Abstract The length of dry beach is an important parameter for the safety and stability of the whole tailings dam. In order to accurately measure the length of dry beach in real time, an efficient, intelligent and accurate online monitoring method based on Mask R-CNN algorithm(instance segmentation algorithm) was proposed. The method is divided into four parts: (1) Installing monitoring cameras on both sides of the tailings dam; (2) Training a network model to recognize the water line and output the coordinates of the water line based on the Mask R-CNN algorithm; (3) Regression analysis was carried out between the contour coordinates of water line and the actual length of dry beach, and the relationship formula of measurement algorithm was fitted; (4) The length of dry beach can be measured in real time by inputting the coordinates of water line into the above formula. The results show that the model can accurately measure the length of dry beach, and is suitable for the conditions of insufficient light, blurred images, rain and snow.

Key words： metrology length of dry beach tailings dam Mask R-CNN algorithm image processing real-time monitoring

Received: 10 June 2019 Published: 08 December 2020

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TB92

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	Articles by authors
	YANG Jun
	SUN Ye-qing
	SHENTU Nan-ying
	LI Qing

Cite this article:

YANG Jun,SUN Ye-qing,SHENTU Nan-ying, et al. Research on Video Measurement of Dry Beach Length of Tailings Pond Based on Mask R-CNN Algorithm[J]. Acta Metrologica Sinica, 2020, 41(12): 1468-1474.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2020.12.04 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2020/V41/I12/1468

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