Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques

Richard Boadu Antwi; Prince Lartey Lawson; Michael Kimollo; Eren Erman Ozguven; Ren Moses; Maxim A. Dulebenets; Thobias Sando

doi:10.3390/ijgi14040135

Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques

Richard Boadu Antwi
, Prince Lartey Lawson
, Michael Kimollo
, Eren Erman Ozguven
, Ren Moses
, Maxim A. Dulebenets
, Thobias Sando

School of Engineering

University of North Florida

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	4
Pages (from-to)	135
Number of pages	1
Journal	ISPRS International Journal of Geo-Information
Volume	14
Issue number	4
DOIs	https://doi.org/10.3390/ijgi14040135
State	Published - Apr 2025

ASJC Scopus Subject Areas

Geography, Planning and Development
Computers in Earth Sciences
Earth and Planetary Sciences (miscellaneous)

Keywords

deep learning (DL)
pavement markings
pedestrian lanes
roadway characteristic index (RCI)
roadway geometry features bicycle lanes

Access to Document

10.3390/ijgi14040135

Cite this

Antwi, R. B., Lawson, P. L., Kimollo, M., Ozguven, E. E., Moses, R., Dulebenets, M. A., & Sando, T. (2025). Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques. ISPRS International Journal of Geo-Information, 14(4), 135. Article 4. https://doi.org/10.3390/ijgi14040135

Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques. / Antwi, Richard Boadu; Lawson, Prince Lartey; Kimollo, Michael et al.
In: ISPRS International Journal of Geo-Information, Vol. 14, No. 4, 4, 04.2025, p. 135.

Research output: Contribution to journal › Article › peer-review

@article{fbff37753b8b48d983d4c0f146251612,

title = "Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques",

keywords = "deep learning (DL), pavement markings, pedestrian lanes, roadway characteristic index (RCI), roadway geometry features bicycle lanes",

author = "Antwi, \{Richard Boadu\} and Lawson, \{Prince Lartey\} and Michael Kimollo and Ozguven, \{Eren Erman\} and Ren Moses and Dulebenets, \{Maxim A.\} and Thobias Sando",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

year = "2025",

month = apr,

doi = "10.3390/ijgi14040135",

language = "English",

volume = "14",

pages = "135",

number = "4",

}

TY - JOUR

T1 - Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques

AU - Antwi, Richard Boadu

AU - Lawson, Prince Lartey

AU - Kimollo, Michael

AU - Ozguven, Eren Erman

AU - Moses, Ren

AU - Dulebenets, Maxim A.

AU - Sando, Thobias

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2025/4

Y1 - 2025/4

KW - deep learning (DL)

KW - pavement markings

KW - pedestrian lanes

KW - roadway characteristic index (RCI)

KW - roadway geometry features bicycle lanes

UR - https://www.scopus.com/pages/publications/105003565874

UR - https://www.scopus.com/pages/publications/105003565874#tab=citedBy

UR - https://www.mendeley.com/catalogue/e80e7870-1a00-3d03-944d-2ee393e87da7/

U2 - 10.3390/ijgi14040135

DO - 10.3390/ijgi14040135

M3 - Article

AN - SCOPUS:105003565874

VL - 14

SP - 135

JO - ISPRS International Journal of Geo-Information

JF - ISPRS International Journal of Geo-Information

IS - 4

M1 - 4

ER -

Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Cite this