Histogram-based road markings extraction by using 3D laser imaging

Wenda Li; Michael Burrow; Yueyue Tao

doi:10.1109/icsens.2018.8589674

Histogram-based road markings extraction by using 3D laser imaging

Wenda Li
, Michael Burrow
, Yueyue Tao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Recent developments in 3D laser technology enable the collection of topographical information over the road surface. Compared with traditional road mapping techniques, laser systems have the advantage of high accuracy, are more efficient and are less affected by climatic conditions. However, the extraction of road markings from 3D laser data in realtime is still challenging due to the high noise content of the data and the requirement to handle large amounts of data. This paper proposes an efficient and low-complexity algorithm to extract the road markings from point cloud 3D laser data by using an optimized multi-threshold algorithm. Data obtained from the field under many conditions have been used to verify the effectiveness of the algorithm. The experimental results indicate that the proposed method provides good results compared to other methods suggested in the literature for similar tasks.

Original language	English
Title of host publication	2018 IEEE SENSORS Proceedings
Publisher	IEEE
Number of pages	4
ISBN (Print)	9781538647073
DOIs	https://doi.org/10.1109/icsens.2018.8589674
Publication status	Published - Oct 2018
Event	17th IEEE Sensors Conference 2018 - Pullman Aeorcity, New Delhi, India Duration: 28 Oct 2018 → 31 Oct 2018

Conference

Conference	17th IEEE Sensors Conference 2018
Abbreviated title	SENSORS 2018
Country/Territory	India
City	New Delhi
Period	28/10/18 → 31/10/18

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10.1109/icsens.2018.8589674

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@inproceedings{ba81f1da591742da9b5e1e9d1a15a200,

title = "Histogram-based road markings extraction by using 3D laser imaging",

abstract = "Recent developments in 3D laser technology enable the collection of topographical information over the road surface. Compared with traditional road mapping techniques, laser systems have the advantage of high accuracy, are more efficient and are less affected by climatic conditions. However, the extraction of road markings from 3D laser data in realtime is still challenging due to the high noise content of the data and the requirement to handle large amounts of data. This paper proposes an efficient and low-complexity algorithm to extract the road markings from point cloud 3D laser data by using an optimized multi-threshold algorithm. Data obtained from the field under many conditions have been used to verify the effectiveness of the algorithm. The experimental results indicate that the proposed method provides good results compared to other methods suggested in the literature for similar tasks.",

author = "Wenda Li and Michael Burrow and Yueyue Tao",

year = "2018",

month = oct,

doi = "10.1109/icsens.2018.8589674",

language = "English",

isbn = "9781538647073",

booktitle = "2018 IEEE SENSORS Proceedings",

publisher = "IEEE",

note = "17th IEEE Sensors Conference 2018, SENSORS 2018 ; Conference date: 28-10-2018 Through 31-10-2018",

}

TY - GEN

T1 - Histogram-based road markings extraction by using 3D laser imaging

AU - Li, Wenda

AU - Burrow, Michael

AU - Tao, Yueyue

PY - 2018/10

Y1 - 2018/10

N2 - Recent developments in 3D laser technology enable the collection of topographical information over the road surface. Compared with traditional road mapping techniques, laser systems have the advantage of high accuracy, are more efficient and are less affected by climatic conditions. However, the extraction of road markings from 3D laser data in realtime is still challenging due to the high noise content of the data and the requirement to handle large amounts of data. This paper proposes an efficient and low-complexity algorithm to extract the road markings from point cloud 3D laser data by using an optimized multi-threshold algorithm. Data obtained from the field under many conditions have been used to verify the effectiveness of the algorithm. The experimental results indicate that the proposed method provides good results compared to other methods suggested in the literature for similar tasks.

AB - Recent developments in 3D laser technology enable the collection of topographical information over the road surface. Compared with traditional road mapping techniques, laser systems have the advantage of high accuracy, are more efficient and are less affected by climatic conditions. However, the extraction of road markings from 3D laser data in realtime is still challenging due to the high noise content of the data and the requirement to handle large amounts of data. This paper proposes an efficient and low-complexity algorithm to extract the road markings from point cloud 3D laser data by using an optimized multi-threshold algorithm. Data obtained from the field under many conditions have been used to verify the effectiveness of the algorithm. The experimental results indicate that the proposed method provides good results compared to other methods suggested in the literature for similar tasks.

U2 - 10.1109/icsens.2018.8589674

DO - 10.1109/icsens.2018.8589674

M3 - Conference contribution

SN - 9781538647073

BT - 2018 IEEE SENSORS Proceedings

PB - IEEE

T2 - 17th IEEE Sensors Conference 2018

Y2 - 28 October 2018 through 31 October 2018

ER -

Histogram-based road markings extraction by using 3D laser imaging

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