Moving Object Detection Under Rain and Snow Weather Conditions

Fig. 2. Qualitative comparison results of different sequences. Blizzard sequence (a) 1096^th frame images; (b) 1111^th frame images; snowfall sequence (c) 807^th frame images; (d) 832^th frame images; sleet sequence (e) 680^th frame images, (f) 688^th frame images; (g) 3249^th frame images in blizzard sequence; (h) 5692^th frame images in skating sequence; (i) snow sequence; (j) ship sequence

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Fig. 3. Influence of different parameters on measured value of F. (a) λ; (b) μ

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Fig. 4. Comparison results of different constraints on different sequences. Snowfall sequence (a) 807^th frame images, (b) 832^th frame images; wet snow sequence (c) 680^th frame images, (d) 688^th frame images

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Table 1. Measurement values of three indicators of different algorithms

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Table 1. Measurement values of three indicators of different algorithms

Image	DECOLOR			TVRPCA			DNLRl1TV			HOSVD			OSTD			Proposed algorithm
Image	P	R	F	P	R	F	P	R	F	P	R	F	P	R	F	P	R	F
Fig.2(a)	0.36	0.96	0.57	0.70	0.47	0.57	0.60	0.61	0.61	0.53	0.71	0.61	0.63	0.69	0.66	0.75	0.85	0.80
Fig.2(b)	0.63	0.34	0.44	0.76	0.26	0.38	0.73	0.67	0.70	0.42	0.80	0.55	0.78	0.62	0.69	0.83	0.81	0.82
Fig.2(c)	0.76	0.57	0.65	0.83	0.51	0.63	0.78	0.60	0.68	0.56	0.70	0.62	0.66	0.69	0.68	0.84	0.78	0.81
Fig.2(d)	0.70	0.79	0.75	0.72	0.71	0.71	0.78	0.81	0.79	0.43	0.47	0.45	0.40	0.43	0.41	0.81	0.89	0.88
Fig.2(e)	0.22	0.75	0.34	0.48	0.71	0.57	0.78	0.80	0.79	0.63	0.86	0.73	0.83	0.77	0.80	0.88	0.93	0.90
Fig.2(f)	0.65	0.73	0.69	0.72	0.78	0.74	0.72	0.79	0.75	0.65	0.80	0.72	0.65	0.83	0.73	0.91	0.94	0.92
Fig.2(g)	0.50	0.51	0.50	0.52	0.43	0.47	0.73	0.85	0.79	0.74	0.85	0.79	0.62	0.82	0.71	0.90	0.91	0.90

Table 2. Comparison of running time of 6 algorithms unit: s

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Table 2. Comparison of running time of 6 algorithms unit: s

Algorithm	Fig.2(a)	Fig.2(b)	Fig.2(c)	Fig.2(d)	Fig.2(e)	Fig.2(f)	Fig.2(g)
Proposed algorithm	27.04	20.31	29.95	21.32	25.03	17.67	21.89
DECOLOR	57.83	46.12	67.90	62.98	71.87	62.95	69.03
TVRPCA	150.23	143.56	163.72	138.53	178.45	167.83	177.93
DNLRL1TV	34.32	19.42	28.43	27.23	36.53	33.38	37.93
HOSVD	62.04	52.42	73.63	62.59	71.58	62.66	58.29
OSTD	30.53	28.34	37.68	42.90	50.06	39.62	35.98

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Guoliang Yang, Dingling Yu, Yang Wang, Yanfang Wang. Moving Object Detection Under Rain and Snow Weather Conditions[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241507

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Paper Information

Category: Machine Vision

Received: May. 8, 2020

Accepted: Jun. 17, 2020

Published Online: Dec. 1, 2020

The Author Email: Dingling Yu (ydl_1001@163.com)

DOI:10.3788/LOP57.241507

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology