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Road Detection and Centerline Extraction Via Deep Recurrent Convolutional Neural Network U-Net
IEEE Transactions on Geoscience and Remote Sensing, 2019Road information extraction based on aerial images is a critical task for many applications, and it has attracted considerable attention from researchers in the field of remote sensing. The problem is mainly composed of two subtasks, namely, road detection and centerline extraction. Most of the previous studies rely on multistage-based learning methods
Xiaofei Yang +5 more
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A research of road centerline extraction algorithm from high resolution remote sensing images
Applications of Digital Image Processing XL, 2017Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images.
Yushan Zhang, Tingfa Xu
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Road network extraction by a higher-order CRF model built on centerline cliques
2015 23rd European Signal Processing Conference (EUSIPCO), 2015The goal of this work is to recover road networks from aerial images. This problem is extremely challenging because roads not only exhibit a highly varying appearance but also are usually occluded by nearby objects. Most importantly, roads are complex structures as they form connected networks of segments with slowly changing width and curvature. As an
O. Besbes, A. Benazza-Benyahia
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Cascaded Multi-Task Road Extraction Network for Road Surface, Centerline, and Edge Extraction
IEEE Transactions on Geoscience and Remote Sensing, 2022Xiaoyan Lu +6 more
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Safety Effectiveness of Centerline Plus Shoulder Rumble Strips on Two-Lane Rural Roads
Journal of Transportation Engineering, 2016The combined application of centerline and shoulder rumble strips is intended to reduce the frequency of crashes by alerting drivers that they are about to leave the traveled lane. To date, this combination treatment has not been rigorously evaluated with a multistate database.
Bhagwant Persaud +3 more
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Journal of Commercial Biotechnology, 2022
In order to improve the recognition efficiency of traffic road centerline recognition method, a traffic road centerline recognition method based on speech recognition technology and image feature extraction is designed. Firstly, the remote sensing image is preprocessed, and then the road knowledge base of traffic road image is established, which mainly
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In order to improve the recognition efficiency of traffic road centerline recognition method, a traffic road centerline recognition method based on speech recognition technology and image feature extraction is designed. Firstly, the remote sensing image is preprocessed, and then the road knowledge base of traffic road image is established, which mainly
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An Integrated Method for Road Network Centerline Detection from Multispectral Imagery
2016Automatic road network detection from multispectral imagery is an effective and economic way to obtain the road and related information. This paper presents an integrated method to extract road network centerline from multispectral imagery. It includes four main steps.
Yuefan Du, Jie Li, Ying Wang
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An Integrated Method for Urban Main-Road Centerline Extraction From Optical Remotely Sensed Imagery
IEEE Transactions on Geoscience and Remote Sensing, 2014Road information has a fundamental role in modern society. Road extraction from optical satellite images is an economic and efficient way to obtain and update a transportation database. This paper presents an integrated method to extract urban main-road centerlines from satellite optical images. The proposed method has four main steps.
Wenzhong Shi, Zelang Miao, Johan Debayle
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ISPRS Journal of Photogrammetry and Remote Sensing, 2016
Abstract Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract ...
Zhenyang Hui +3 more
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Abstract Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract ...
Zhenyang Hui +3 more
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Iterative and Localized Radon Transform for Road Centerline Detection from Classified Imagery
2007An iterative and localized Radon transform is proposed in this paper for the specific application of road network extraction from high resolution satellite imagery. Based on an accurate estimation of the line width and line parameters in the radon space, the localized Radon transform makes it possible to detect the small road segments and the long ...
Isabelle Couloigner, Qiaoping Zhang
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