Automatic drawing for traffic marking with MMS LIDAR intensity
Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore...
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doaj-12fb58f1293a4bf7a903a885378d104f2020-11-25T01:39:11ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502014-05-01II-536337010.5194/isprsannals-II-5-363-2014Automatic drawing for traffic marking with MMS LIDAR intensityG. Takahashi0H. Takeda1Y. Shimano2Spatial Information Division, Kokusai Kogyo Co., Ltd., Tokyo, JapanSpatial Information Division, Kokusai Kogyo Co., Ltd., Tokyo, JapanSpatial Information Division, Kokusai Kogyo Co., Ltd., Tokyo, JapanUpgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings. However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points; (3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5) Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines to generate automated traffic marking mapping data.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5/363/2014/isprsannals-II-5-363-2014.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Takahashi H. Takeda Y. Shimano |
spellingShingle |
G. Takahashi H. Takeda Y. Shimano Automatic drawing for traffic marking with MMS LIDAR intensity ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
G. Takahashi H. Takeda Y. Shimano |
author_sort |
G. Takahashi |
title |
Automatic drawing for traffic marking with MMS LIDAR intensity |
title_short |
Automatic drawing for traffic marking with MMS LIDAR intensity |
title_full |
Automatic drawing for traffic marking with MMS LIDAR intensity |
title_fullStr |
Automatic drawing for traffic marking with MMS LIDAR intensity |
title_full_unstemmed |
Automatic drawing for traffic marking with MMS LIDAR intensity |
title_sort |
automatic drawing for traffic marking with mms lidar intensity |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2014-05-01 |
description |
Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of
Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a
framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual
human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an
efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings.
However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual
operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners
are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using
MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local
reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a
highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by
intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points;
(3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5)
Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines
using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines
to generate automated traffic marking mapping data. |
url |
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5/363/2014/isprsannals-II-5-363-2014.pdf |
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AT gtakahashi automaticdrawingfortrafficmarkingwithmmslidarintensity AT htakeda automaticdrawingfortrafficmarkingwithmmslidarintensity AT yshimano automaticdrawingfortrafficmarkingwithmmslidarintensity |
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