Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
| Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression | |
Cheng, Guangliang ; Zhu, Feiyun; Xiang, Shiming; Pan, Chunhong; Cheng GL(程光亮)
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| Source Publication | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
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| 2016-04-01 | |
| Volume | 13Issue:4Pages:545-549 |
| Subtype | Article |
| Abstract | Accurate 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. |
| Keyword | Multidirection Nonmaximum Suppression (M-nms) Multiscale Filtering (Mf) Road Centerline Extraction Semisupervised Segmentation |
| WOS Headings | Science & Technology ; Physical Sciences ; Technology |
| DOI | 10.1109/LGRS.2016.2524025 |
| WOS Keyword | SHAPE-FEATURES ; IMAGERY ; CLASSIFICATION |
| Indexed By | SCI |
| Language | 英语 |
| Funding Organization | Natural Science Foundation of China(91338202 ; 91438105 ; 61305049 ; 61370039) |
| WOS Research Area | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS Subject | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS ID | WOS:000373009800015 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://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 Author | Cheng GL(程光亮) |
| Affiliation | Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China |
| First Author Affilication | Chinese 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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| IGRSL_final_submissi（1560KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
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