CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression
Cheng, Guangliang; Zhu, Feiyun; Xiang, Shiming; Pan, Chunhong; Cheng GL(程光亮)
Source PublicationIEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2016-04-01
Volume13Issue:4Pages:545-549
SubtypeArticle
AbstractAccurate road centerline extraction from remotely sensed images plays a significant role in road map generation and updating. In the road extraction problem, the acquisition of labeled data is time consuming and costly; thus, there are only a small amount of labeled samples in reality. In the existing centerline extraction algorithms, the thinning-based algorithms always produce small spurs that reduce the smoothness and accuracy of the road centerline; the regression-based algorithms can extract a smooth road network, but they are time consuming. To solve the aforementioned problems, we propose a novel road centerline extraction method, which is constructed based on semi-supervised segmentation and multiscale filtering (MF) and multidirection nonmaximum suppression (M-NMS) (MF&M-NMS). Specifically, a semisupervised method, which explores the intrinsic structures between the labeled samples and the unlabeled ones, is introduced to obtain the segmentation result. Then, a novel MF&M-NMS-based algorithm is proposed to gain a smooth and complete road centerline network. Experimental results on a public data set demonstrate that the proposed method achieves comparable or better performances by comparing with the stateof-the-art methods. In addition, our method is nearly ten times faster than the state-of-the-art methods.
KeywordMultidirection Nonmaximum Suppression (M-nms) Multiscale Filtering (Mf) Road Centerline Extraction Semisupervised Segmentation
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.1109/LGRS.2016.2524025
WOS KeywordSHAPE-FEATURES ; IMAGERY ; CLASSIFICATION
Indexed BySCI
Language英语
Funding OrganizationNatural Science Foundation of China(91338202 ; 91438105 ; 61305049 ; 61370039)
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000373009800015
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12189
Collection模式识别国家重点实验室_先进数据分析与学习
Corresponding AuthorCheng GL(程光亮)
AffiliationChinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Cheng, Guangliang,Zhu, Feiyun,Xiang, Shiming,et al. Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2016,13(4):545-549.
APA Cheng, Guangliang,Zhu, Feiyun,Xiang, Shiming,Pan, Chunhong,&程光亮.(2016).Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,13(4),545-549.
MLA Cheng, Guangliang,et al."Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 13.4(2016):545-549.
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