Results 171 to 180 of about 26,498 (203)

Multiscale road centerlines extraction from high-resolution aerial imagery

Neurocomputing, 2019
Abstract Accurate road extraction from high-resolution aerial imagery has many applications such as urban planning and vehicle navigation system. The common road extraction methods are based on classification algorithm, which needs to design robust handcrafted features for road. However, designing such features is difficult.
Ruyi Liu, Qiguang Miao, Jianfeng Song, Yining Quan, Yunan Li, Pengfei Xu, Jing Dai   +6 more
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A Wavelet Transform Based Method for Road Centerline Extraction

Photogrammetric Engineering & Remote Sensing, 2004
This paper introduces a new wavelet transform based method of road centerline extraction from high resolution remote sensing images. In the one dimensional case, we characterize different kinds of sudden changes of signals by comparing the magnitudes of the local extreme values of the wavelet transforms under different dilation scales of the same ...
Tieling Chen, Jinfei Wang, Kaizhong Zhang   +2 more
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Area Collapse and Road Centerlines based on Straight Skeletons

GeoInformatica, 2007
Skeletonization of polygons is a technique, which is often applied to problems of cartography and geographic information science. Especially it is needed for generalization tasks such as the collapse of small or narrow areas, which are negligible for a certain scale. Different skeleton operators can be used for such tasks.
Jan-Henrik Haunert, Monika Sester
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Road Centerline Data Accumulation for Rescue Workers Whose Expertise Is Not GIS

Disaster Medicine and Public Health Preparedness, 2020
ABSTRACTObjectives:The objective of this study is to provide road centerline data for professionals of disaster medicine areas who are often beginners in GIS use.Methods:Newly developed vector tile format data were converted into shapefile format data, then were organized as second level medical districts to which medical professionals are accustomed ...
Kanetoshi, Hattori, Ritsuko, Hattori, Hiromi, Taneichi, Chiaki, Funada, Junko, Ouchi, Hitomi, Watanabe, Eriko, Tane   +6 more
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Road Centerlines Extraction from High Resolution Remote Sensing Image

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
The acquisition of road network information based on high-resolution remote sensing images has important practical application value. This paper focus on the phenomenon of complex background influence and easily produce spurs around the true road centerlines, the method of using convolutional neural network for road region extraction and segmental ...
Shikai Sun, Wei Xia, Bingqi Zhang, Ying Zhang   +3 more
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A new approach for road centerlines extraction and width estimation

IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, 2010
Road centerlines detection and the estimation of road widths play an important role in many computer vision applications e.g. road network extraction from satellite images. Canny edge detector has many advantages over other first-order edge detection algorithm.
Junzhi Guan, Zongyi Wang, Xiaochen Yao
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A Modified Road Centerlines Search Method from Remote Sensing Images

2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC), 2017
Aiming at the sensitivity of the road centerline extraction algorithm using directional texture to the disturbance in the images, a modified method for road centerlines on high-resolution remote sensing images is proposed based on the directional texture and Kalman Filter.
Du Juan, Li Runsheng, Jin Fei
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A Semi-Automatic Method for Road Centerline Extraction From VHR Images

IEEE Geoscience and Remote Sensing Letters, 2014
This letter presents a semi-automatic approach to delineating road networks from very high resolution satellite images. The proposed method consists of three main steps. First, the geodesic method is used to extract the initial road segments that link the road seed points prescribed in advance by users. Next, a road probability map is produced based on
Zelang Miao, Bin Wang, Wenzhong Shi, Hua Zhang   +3 more
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Spectral–Spatial Classification and Shape Features for Urban Road Centerline Extraction

IEEE Geoscience and Remote Sensing Letters, 2014
This letter presents a two-step method for urban main road extraction from high-resolution remotely sensed imagery by integrating spectral-spatial classification and shape features. In the first step, spectral-spatial classification segments the imagery into two classes, i.e., the road class and the nonroad class, using path openings and closings.
null Wenzhong Shi, null Zelang Miao, null Qunming Wang, null Hua Zhang   +3 more
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End-to-End Road Centerline Extraction via Learning a Confidence Map

2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS), 2018
Road extraction from aerial and satellite image is one of complex and challenging tasks in remote sensing field. The task is required for a wide range of application, such as autonomous driving, urban planning and automatic mapping for GIS data collection.
Wei Yujun, Hu Xiangyun, Gong Jinqi
openaire   +1 more source