• Laser & Optoelectronics Progress
  • Vol. 55, Issue 11, 111002 (2018)
Shenru Xie1, Shengbo Ye1, Baohua Yang1、2、*, Xuemei Wang1, and Hongxia He1
Author Affiliations
  • 1 School of Information and Computer, Anhui Agriculture University, Hefei, Anhui 230036, China
  • 2 Key Laboratory of Technology Integration and Application in Agricultural Internet of Things,Ministry of Agriculture, Hefei, Anhui 230036, China
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    DOI: 10.3788/LOP55.111002 Cite this Article Set citation alerts
    Shenru Xie, Shengbo Ye, Baohua Yang, Xuemei Wang, Hongxia He. Moving Target Detection Based on Improved YUV_Vibe Fusion Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111002 Copy Citation Text show less
    Schematic of neighborhood extraction
    Fig. 1. Schematic of neighborhood extraction
    Background model of Vibe
    Fig. 2. Background model of Vibe
    Flow chart of the algorithm
    Fig. 3. Flow chart of the algorithm
    Foreground detection. (a) Detection result of model 1; (b) detection area of model 2
    Fig. 4. Foreground detection. (a) Detection result of model 1; (b) detection area of model 2
    Outdoor target detection effects of all algorithms. (a)(f) Original image sequences; (b)(g) results of frame difference method; (c)(h) results of Gaussian mixture model method; (d)(i) results of Vibe method; (e)(j) results of improved method
    Fig. 5. Outdoor target detection effects of all algorithms. (a)(f) Original image sequences; (b)(g) results of frame difference method; (c)(h) results of Gaussian mixture model method; (d)(i) results of Vibe method; (e)(j) results of improved method
    Comparison of the shadow experimental results. (a) Original image sequence; (b) Vibe method; (c) improved method
    Fig. 6. Comparison of the shadow experimental results. (a) Original image sequence; (b) Vibe method; (c) improved method
    Comparison of the ghost experimental results. (a) Original image of 427th frame; (d) original image of 525th frame; (b)(e) results of Vibe method; (c)(f) results of improved method
    Fig. 7. Comparison of the ghost experimental results. (a) Original image of 427th frame; (d) original image of 525th frame; (b)(e) results of Vibe method; (c)(f) results of improved method
    MethodPFPRFrame /s
    Vibe0.73470.031236
    YUV_Vibe0.83180.021828
    Table 1. Appraisal result of all algorithms
    Shenru Xie, Shengbo Ye, Baohua Yang, Xuemei Wang, Hongxia He. Moving Target Detection Based on Improved YUV_Vibe Fusion Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111002
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