Ground-based cloud classification by learning stable local binary patterns
Wang, Yu1,2,3; Shi, Cunzhao1; Wang, Chunheng1; Xiao, Baihua1
2018-07-15
发表期刊ATMOSPHERIC RESEARCH
卷号207页码:74-89
文章类型Article
摘要Feature selection and extraction is the first step in implementing pattern classification. The same is true for ground-based cloud classification. Histogram features based on local binary patterns (LBPs) are widely used to classify texture images. However, the conventional uniform LBP approach cannot capture all the dominant patterns in cloud texture images, thereby resulting in low classification performance. In this study, a robust feature extraction method by learning stable LBPs is proposed based on the averaged ranks of the occurrence frequencies of all rotation invariant patterns defined in the LBPs of cloud images. The proposed method is validated with a ground-based cloud classification database comprising five cloud types. Experimental results demonstrate that the proposed method achieves significantly higher classification accuracy than the uniform LBP, local texture patterns (LTP), dominant LBP (DLBP), completed LBP (CLTP) and salient LBP (SaLBP) methods in this cloud image database and under different noise conditions. And the performance of the proposed method is comparable with that of the popular deep convolutional neural network (DCNN) method, but with less computation complexity. Furthermore, the proposed method also achieves superior performance on an independent test data set.
关键词Local Binary Patterns Cloud Classification Feature Selection And Extraction Texture Image
WOS标题词Science & Technology ; Physical Sciences
DOI10.1016/j.atmosres.2018.02.023
关键词[WOS]INVARIANT TEXTURE CLASSIFICATION ; CEILOMETER MEASUREMENTS ; SOLAR IRRADIANCE ; FACE RECOGNITION ; TROPICAL REGION ; IMAGE FEATURES ; SKY IMAGES ; COVER ; SEGMENTATION ; ALGORITHMS
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China (NSFC)(61531019 ; 61601462 ; 61503228 ; 71621002)
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
WOS记录号WOS:000430901800006
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22036
专题复杂系统管理与控制国家重点实验室_影像分析与机器视觉
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Shanxi Univ, Sch Software, Taiyuan 030006, Shanxi, Peoples R China
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Wang, Yu,Shi, Cunzhao,Wang, Chunheng,et al. Ground-based cloud classification by learning stable local binary patterns[J]. ATMOSPHERIC RESEARCH,2018,207:74-89.
APA Wang, Yu,Shi, Cunzhao,Wang, Chunheng,&Xiao, Baihua.(2018).Ground-based cloud classification by learning stable local binary patterns.ATMOSPHERIC RESEARCH,207,74-89.
MLA Wang, Yu,et al."Ground-based cloud classification by learning stable local binary patterns".ATMOSPHERIC RESEARCH 207(2018):74-89.
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