面向视频图像的烟雾检测算法综述 
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Review on Smoke Detection Algorithms for Video Images
图 & 表
图 1. 面向视频图像的烟雾检测流程
Fig. 1. Flow chart of smoke detection for video images
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图 2. 烟雾运动方向估计的离散示意图[52]
Fig. 2. Discrete diagram for estimating smoke motion direction [52]
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图 3. 不同场景下的烟雾检测例子[15]
Fig. 3. Examples for smoke detection under different scenes[15]
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图 4. 基于多特征融合的烟雾检测
Fig. 4. Smoke detection based on multi-feature fusion
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表 1纹理特征的统计度量参数计算公式
Table1. Formulas for calculating statistical metric parameters of texture features
| Metric parameter | Formula |
|---|
| Mean | μ=x1(a) | | Uniformity | U=(a) | | Entropy | E=-Qa(ln Qa) | | Standard deviation | σ= |
|
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表 2表征GLCM的统计参数[32]
Table2. Statistical parameters for characterizing GLCM[32]
| Parameter | Formula |
|---|
| Energy | AASM=P(e,f)2 | | Contrast | CCON=(e-f)2P(e,f) | | Correlation | CCOR= | | Homogeneity | IIDM=P(e,f) |
|
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表 3面向视频图像的烟雾检测算法
Table3. Smoke detection algorithm for video images
| Method | Pre-processing | Smoke feature | Classification | Accuracy/% | Falsepositive/% | Falsenegative/% |
|---|
| Method inRef. [57] | Color segmentation technique | Texture, energy, and motion | Neural network(NN) | 80 | - | - | | Method inRef. [15] | Color segmentation technique | Energy and texture | SVM | 96.29 | 3.71 | 1.74 | | Method inRef. [5] | Motion segmentation technique | Color , fuzzy feature, shape irregularity, and motion | PSO-SVM | 97.16 | 2.84 | - | | Method inRef. [52] | Motion segmentation technique | Color, texture, energy, HOG feature, shape irregularity, and motion | AdaBoost-RBFSVM | 91.25 | 0.31 | - | | Method inRef. [67] | Motion segmentation technique | Shape irregularity, diffusion property, and texture | ANFIS-Bayes-MR | 99.09 | 1.94 | - |
|
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表 4不同深度学习网络模型的视频图像烟雾检测结果
Table4. Smoke detection results for video images based on different deep learning network models
| Reference | Network model | Accuracy/% | False positive/% |
|---|
| Method in Ref. [89] | Deep normalization and CNN(14 layers) | 97.52 | 0.6 | | Method in Ref. [90] | RCNN+3D CNN | 95.23 | 0.39 | | Method in Ref. [91] | CNN(AlexNet) | 99.44 | 0.44 | | Method in Ref. [92] | CaffeNet CNN | 98 | 1.7 | | Method in Ref. [93] | DN-CNN | 96.37 | 0.60 | | Method in Ref. [87] | YOLOv2 | 94.7 | 5.2 | | Method in Ref. [87] | GMM+YOLOv2 | 98.1 | 0.8 |
|
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陈长友, 杨健晟. 面向视频图像的烟雾检测算法综述[J]. 激光与光电子学进展, 2021, 58(4): 0400003. Changyou Chen, Jiansheng Yang. Review on Smoke Detection Algorithms for Video Images[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0400003.
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