Determine distances area of traffic lights using image processing algorithms

Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors a...

Full description

Saved in:
Bibliographic Details
Published inAIP conference proceedings Vol. 2547; no. 1
Main Authors Touma, Teeba A., Abbas, Heba Kh, Saleh, Anwar H. Al, Mohamad, Haidar J., Al-Zuky, Ali A.
Format Journal Article Conference Proceeding
LanguageEnglish
Published Melville American Institute of Physics 02.12.2022
Subjects
Online AccessGet full text
ISSN0094-243X
1551-7616
DOI10.1063/5.0113085

Cover

Abstract Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors and calculate area of the signals. The Three colors (red, green, and yellow) distinguished by threshold for each color red, blue, green, and grayscale to give accurate results. The distance between the camera (car) and the traffic light is determined by scale factor (SCF) equation. The real dimension of the traffic measured manually and converted to pixel to calculate the area of each color. The area of each light within the traffic estimated by morphology method. Thus, the light traffic and the area is determined, and the distance between the traffic light and car is determined. The results show that the behavior of the area and distance of the traffic with the video frame shows logic data in pixel domain. Moreover, the light separation is accurate 100% according to the suggested algorithm.
AbstractList Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors and calculate area of the signals. The Three colors (red, green, and yellow) distinguished by threshold for each color red, blue, green, and grayscale to give accurate results. The distance between the camera (car) and the traffic light is determined by scale factor (SCF) equation. The real dimension of the traffic measured manually and converted to pixel to calculate the area of each color. The area of each light within the traffic estimated by morphology method. Thus, the light traffic and the area is determined, and the distance between the traffic light and car is determined. The results show that the behavior of the area and distance of the traffic with the video frame shows logic data in pixel domain. Moreover, the light separation is accurate 100% according to the suggested algorithm.
Author Abbas, Heba Kh
Al-Zuky, Ali A.
Touma, Teeba A.
Mohamad, Haidar J.
Saleh, Anwar H. Al
Author_xml – sequence: 1
  givenname: Teeba A.
  surname: Touma
  fullname: Touma, Teeba A.
  organization: Department of Physics, College of Science for Women, University of Baghdad
– sequence: 2
  givenname: Heba Kh
  surname: Abbas
  fullname: Abbas, Heba Kh
  organization: Department of Physics, College of Science for Women, University of Baghdad
– sequence: 3
  givenname: Anwar H. Al
  surname: Saleh
  fullname: Saleh, Anwar H. Al
  organization: Department of computer science, College of Science, Mustansiriyah University
– sequence: 4
  givenname: Haidar J.
  surname: Mohamad
  fullname: Mohamad, Haidar J.
  organization: Department of physics, College of Science, Mustansiriyah University
– sequence: 5
  givenname: Ali A.
  surname: Al-Zuky
  fullname: Al-Zuky, Ali A.
  organization: Department of physics, College of Science, Mustansiriyah University
BookMark eNp9kE9LAzEUxINUsK0e_AYBb8LWvM0mmxyl_oWCFwVvIbubbFPaZE1SwW_vagvePD0YfjNvmBma-OANQpdAFkA4vWELAkCJYCdoCoxBUXPgEzQlRFZFWdH3MzRLaUNIKetaTNHqzmQTd84b3LmUtW9NwjoajYPFOWprXYu3rl_nhPfJ-R67ne4NHmIYyV9Bb_sQXV7v0jk6tXqbzMXxztHbw_3r8qlYvTw-L29XxQBc5MIA5a22jTENpwQawjotRNXIptTCMCY0LWktJTBru6Zq2o7XQjLWCSsqWQKdo6tD7tjiY29SVpuwj358qcq6YsCgJnKkrg9Ual3W2QWvhji2j1_qM0TF1HEpNXT2PxiI-pn2z0C_AYrtbP4
CODEN APCPCS
ContentType Journal Article
Conference Proceeding
Copyright Author(s)
2022 Author(s). Published by AIP Publishing.
Copyright_xml – notice: Author(s)
– notice: 2022 Author(s). Published by AIP Publishing.
DBID 8FD
H8D
L7M
DOI 10.1063/5.0113085
DatabaseName Technology Research Database
Aerospace Database
Advanced Technologies Database with Aerospace
DatabaseTitle Technology Research Database
Aerospace Database
Advanced Technologies Database with Aerospace
DatabaseTitleList
Technology Research Database
DeliveryMethod fulltext_linktorsrc
Discipline Physics
EISSN 1551-7616
Editor Al-Kaabi, Mohammed Abdulhussain
Hashim, Jasim Hanoon
Joda, Baker A.
Abdulateef, Ahmed Mahmood
Mohammed, Adnan Ibrahim
Madlool, Thaer Mahdi
Abdulmunem, Ashwan A.
Editor_xml – sequence: 1
  givenname: Jasim Hanoon
  surname: Hashim
  fullname: Hashim, Jasim Hanoon
  organization: University of Kerbala College of Science
– sequence: 2
  givenname: Baker A.
  surname: Joda
  fullname: Joda, Baker A.
  organization: University of Kerbala
– sequence: 3
  givenname: Ahmed Mahmood
  surname: Abdulateef
  fullname: Abdulateef, Ahmed Mahmood
  organization: University of Kerbala College of Science
– sequence: 4
  givenname: Thaer Mahdi
  surname: Madlool
  fullname: Madlool, Thaer Mahdi
  organization: University of Kerbala College of Science
– sequence: 5
  givenname: Adnan Ibrahim
  surname: Mohammed
  fullname: Mohammed, Adnan Ibrahim
  organization: University of Kerbala College of Science
– sequence: 6
  givenname: Mohammed Abdulhussain
  surname: Al-Kaabi
  fullname: Al-Kaabi, Mohammed Abdulhussain
  organization: University of Kerbala
– sequence: 7
  givenname: Ashwan A.
  surname: Abdulmunem
  fullname: Abdulmunem, Ashwan A.
  organization: University of Kerbala
ExternalDocumentID acp
Genre Conference Proceeding
GroupedDBID -~X
23M
5GY
AAAAW
AABDS
AAEUA
AAPUP
AAYIH
ABJNI
ACBRY
ACZLF
ADCTM
AEJMO
AFATG
AFHCQ
AGKCL
AGLKD
AGMXG
AGTJO
AHSDT
AJJCW
ALEPV
ALMA_UNASSIGNED_HOLDINGS
ATXIE
AWQPM
BPZLN
F5P
FDOHQ
FFFMQ
HAM
M71
M73
RIP
RQS
SJN
~02
8FD
ABJGX
ADMLS
H8D
L7M
ID FETCH-LOGICAL-p168t-e136cafbeeb6301b05da884b9b2a8e558a32379915ffdb4bcd678955d8f849213
ISSN 0094-243X
IngestDate Mon Jun 30 02:32:25 EDT 2025
Fri Jun 21 00:13:08 EDT 2024
Tue Jul 04 19:17:49 EDT 2023
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
License 0094-243X/2022/2547/050004/9/$30.00
Published by AIP Publishing.
LinkModel OpenURL
MeetingName THE 9TH INTERNATIONAL CONFERENCE ON APPLIED SCIENCE AND TECHNOLOGY (ICAST 2021)
MergedId FETCHMERGED-LOGICAL-p168t-e136cafbeeb6301b05da884b9b2a8e558a32379915ffdb4bcd678955d8f849213
Notes ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
PQID 2745151709
PQPubID 2050672
PageCount 9
ParticipantIDs scitation_primary_10_1063_5_0113085
proquest_journals_2745151709
PublicationCentury 2000
PublicationDate 20221202
PublicationDateYYYYMMDD 2022-12-02
PublicationDate_xml – month: 12
  year: 2022
  text: 20221202
  day: 02
PublicationDecade 2020
PublicationPlace Melville
PublicationPlace_xml – name: Melville
PublicationTitle AIP conference proceedings
PublicationYear 2022
Publisher American Institute of Physics
Publisher_xml – name: American Institute of Physics
References Shi, Zou, Zhang (c7) 2016; 17
Yoneda (c5) 2020; 20
Abbas, Kh (c16) 2019; 571
Ahmed, Ahmad, Khan, Asif (c18) 2020; 8
Kareem, Jabbar (c4) 2018; 44
Heba, Abass Anwar, Al-Saleh, Al-Zuky (c17) 2015; 6
Bouktif, Cheniki, Ouni (c6) 2021; 21
Nioche (c10) 2018; 78
Uhl, Leyk, Chiang, Duan, Knoblock (c13) 2018; 7
Leal, Soares, De Almeida, Chung (c3) 2017; 25
Wang (c15) 2019; 90
Senthilkumaran, Thimmiaraja (c14) 2014; 5
References_xml – volume: 90
  start-page: 033701
  year: 2019
  ident: c15
  article-title: Super-resolution imaging and field of view extension using a single camera with Risley prisms
  publication-title: Review of Scientific Instruments
– volume: 8
  start-page: 136361
  year: 2020
  ident: c18
  publication-title: Comparison of Deep-Learning-Based Segmentation Models: Using Top View Person Images
– volume: 21
  start-page: 2302
  year: 2021
  ident: c6
  article-title: Traffic signal control using hybrid action space deep reinforcement learning
  publication-title: Sensors
– volume: 25
  start-page: 1769
  year: 2017
  ident: c3
  article-title: Active control for traffic lights in regions and corridors: an approach based on evolutionary computation
  publication-title: Transportation research procedia
– volume: 44
  start-page: 11
  year: 2018
  ident: c4
  article-title: Design and Implementation Smart Traffic Light Using GSM and IR
  publication-title: Iraqi Journal for Computers and Informatics
– volume: 17
  start-page: 690
  year: 2016
  ident: c7
  article-title: Real-Time Traffic Light Detection with Adaptive Background Suppression Filter
  publication-title: IEEE Transactions on Intelligent Transportation Systems
– volume: 6
  start-page: 497
  year: 2015
  ident: c17
  article-title: Estimate Mathematical Model to Calculate the View Angle Depending on the Camera Zoom
  publication-title: International Journal of Scientific & Engineering Research
– volume: 78
  start-page: 4786
  year: 2018
  ident: c10
  article-title: LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity
  publication-title: Cancer research
– volume: 7
  year: 2018
  ident: c13
  article-title: Map Archive Mining: Visual-Analytical Approaches to Explore Large Historical Map Collections
  publication-title: ISPRS Int. J. Geo-Inf.
– volume: 571
  year: 2019
  ident: c16
  article-title: Modelling vision angles of optical camera zoom using image processing algorithm
  publication-title: IOP Conference Series: Materials Science and Engineering.
– volume: 20
  start-page: 1181
  year: 2020
  ident: c5
  article-title: Robust traffic light and arrow detection using digital map with spatial prior information for automated driving
  publication-title: Sensors
– volume: 5
  start-page: 2684
  year: 2014
  ident: c14
  article-title: An Illustrative Analysis of Mathematical Morphology Operations for MRI Brain Images
  publication-title: Journal of Computer Science and Information Technologies.
SSID ssj0029778
Score 2.311464
Snippet Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the...
SourceID proquest
scitation
SourceType Aggregation Database
Enrichment Source
Publisher
SubjectTerms Algorithms
Color
Image processing
Light
Mathematical analysis
Object recognition
Pixels
Traffic signals
Title Determine distances area of traffic lights using image processing algorithms
URI http://dx.doi.org/10.1063/5.0113085
https://www.proquest.com/docview/2745151709
Volume 2547
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1bS8MwFMeDTkTfvOKdgL6N6tokvTwOp6jMC7jB3kLSJiroNrbqg5_ekzRrNx2CvpRSQjfOLyT_k54LQieM6swoT08HUejR1LR5ybTwkkwRlvhSk9ScQ97ehVddetNjvaqFos0uyeVp-jk3r-Q_VOEZcDVZsn8gW74UHsA98IUrEIbrT8Zzt5rm9YMJHJ8Ui63GjKfnQsvFvCjzPSY3nMd1AWrRBgiMhKkiUX81Xvq4_m7PDl7eTCjPsEgisGmMr0-D0Uv-_DZzTBDYjiWNyqksv__MxCDYKNN0-lQQvD0voLZFL2wPbk1kvheFRUrkZNEEvzL6Pj1-rMYgf8CEpi4q7JRFZ57Zitd39_yy227zzkWvs4iWAhLFjRpaarZu24-l2wwKtdhP3V-b1IcKyVn56hn_YAXEQxHHMCUVOmtoq0qixA8lj3W0oPobaNnZYhO1Syi4hIINFDzQ2EHBBRRsoWALBVdQcAVlC3UvLzrnV55rbeEN_TDOPeWTMBVaKiVDWGJlg2UijqlMZCBixVgsCBgDtDvTOpNUphmIioSxLNYxTQKfbKNaf9BXOwhTKZQSyghx0zdFShgFPqWihIrUj8guOpiYhru5O-ZBREHI-lEj2UXHpbn4sKhwwm1kQkg4486-c0d9DEbVCD7M9N7vP7WPVquZeYBq-ehdHYKky-WRY_4FhVdQtw
linkProvider EBSCOhost
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=AIP+conference+proceedings&rft.atitle=Determine+distances+area+of+traffic+lights+using+image+processing+algorithms&rft.date=2022-12-02&rft.pub=American+Institute+of+Physics&rft.issn=0094-243X&rft.eissn=1551-7616&rft.volume=2547&rft.issue=1&rft_id=info:doi/10.1063%2F5.0113085&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0094-243X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0094-243X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0094-243X&client=summon