Rail Detection Based on LSD and the Least Square Curve Fitting

It is necessary to rely on the rail gauge to determine whether the object beside the track will affect train operation safety or not. A convenient and fast method based on line segment detector (LSD) and the least square curve fitting to identify the rail in the image is proposed in this paper. The...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Machine intelligence research (Print) Jg. 18; H. 1; S. 85 - 95
Hauptverfasser: Zheng, Yun-Shui, Jin, Yan-Wei, Dong, Yu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beijing Springer Nature B.V 01.02.2021
Schlagworte:
Accuracy
Algorithms
Approximation
Automation
Cameras
Curve fitting
Least squares
Mathematical models
Real time
Robustness (mathematics)
Segments
ISSN:2153-182X, 2153-1838
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract It is necessary to rely on the rail gauge to determine whether the object beside the track will affect train operation safety or not. A convenient and fast method based on line segment detector (LSD) and the least square curve fitting to identify the rail in the image is proposed in this paper. The image in front of the train can be obtained through the camera on-board. After preprocessing, it will be divided equally along the longitudinal axis. Utilizing the characteristics of the LSD algorithm, the edges are approximated into multiple line segments. After screening the terminals of the line segments, it can generate the mathematical model of the rail in the image based on the least square. Experiments show that the algorithm in this paper can fit the rail curve accurately and has good applicability and robustness.
AbstractList It is necessary to rely on the rail gauge to determine whether the object beside the track will affect train operation safety or not. A convenient and fast method based on line segment detector (LSD) and the least square curve fitting to identify the rail in the image is proposed in this paper. The image in front of the train can be obtained through the camera on-board. After preprocessing, it will be divided equally along the longitudinal axis. Utilizing the characteristics of the LSD algorithm, the edges are approximated into multiple line segments. After screening the terminals of the line segments, it can generate the mathematical model of the rail in the image based on the least square. Experiments show that the algorithm in this paper can fit the rail curve accurately and has good applicability and robustness.
Author Dong, Yu
Zheng, Yun-Shui
Jin, Yan-Wei
Author_xml – sequence: 1
  givenname: Yun-Shui
  surname: Zheng
  fullname: Zheng, Yun-Shui
– sequence: 2
  givenname: Yan-Wei
  surname: Jin
  fullname: Jin, Yan-Wei
– sequence: 3
  givenname: Yu
  surname: Dong
  fullname: Dong, Yu
BookMark eNo9jUFLwzAYQINMcM79AG8Bz9HvS9I0uQjabSoUBKfgbWTpV-0YqWtSf78DxdN7p_fO2ST2kRi7RLhGgPImIRqlBEgQKDUKfcKmEgsl0Co7-Xf5fsbmKe0AQCkJxqkpu33x3Z4vKFPIXR_5vU_U8KPU6wX3seH5k3hNPmW-Pox-IF6NwzfxVZdzFz8u2Gnr94nmf5yxt9XytXoU9fPDU3VXi6ARsrBOBd1AwHLrCxla3ThbWkemNejJSI-arDFBbQtqy6awZCE4L6UvNJWW1Ixd_Xa_hv4wUsqbXT8O8bjcSIfWWAvSqB8DKEvI
CitedBy_id crossref_primary_10_1109_TIM_2024_3387496
crossref_primary_10_3390_electronics10162038
crossref_primary_10_1016_j_measurement_2023_113567
crossref_primary_10_3390_drones9010037
crossref_primary_10_1109_TVT_2021_3133327
crossref_primary_10_1016_j_istruc_2024_107808
crossref_primary_10_1016_j_engappai_2025_111527
crossref_primary_10_1088_1361_6501_add6c3
crossref_primary_10_3390_app14072795
crossref_primary_10_1109_TIM_2023_3324678
crossref_primary_10_1177_21925682241282581
crossref_primary_10_1002_tee_24012
ContentType Journal Article
Copyright Institute of Automatinn, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2020.
Copyright_xml – notice: Institute of Automatinn, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2020.
DBID 8FE
8FG
AFKRA
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
GNUQQ
HCIFZ
JQ2
K7-
P5Z
P62
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
DOI 10.1007/s11633-020-1241-4
DatabaseName ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central UK/Ireland
Advanced Technologies & Computer Science Collection
ProQuest Central Essentials
AUTh Library subscriptions: ProQuest Central
Technology Collection
ProQuest One
ProQuest Central
ProQuest Central Student
SciTech Premium Collection
ProQuest Computer Science Collection
Computer Science Database
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
DatabaseTitle Advanced Technologies & Aerospace Collection
Computer Science Database
ProQuest Central Student
Technology Collection
ProQuest One Academic Middle East (New)
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Computer Science Collection
ProQuest One Academic Eastern Edition
SciTech Premium Collection
ProQuest One Community College
ProQuest Technology Collection
ProQuest SciTech Collection
ProQuest Central
Advanced Technologies & Aerospace Database
ProQuest One Applied & Life Sciences
ProQuest One Academic UKI Edition
ProQuest Central Korea
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
DatabaseTitleList Advanced Technologies & Aerospace Collection
Database_xml – sequence: 1
  dbid: P5Z
  name: Advanced Technologies & Aerospace Database
  url: https://search.proquest.com/hightechjournals
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
EISSN 2153-1838
EndPage 95
GroupedDBID 8FE
8FG
AFFHD
AFKRA
ALMA_UNASSIGNED_HOLDINGS
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
GNUQQ
HCIFZ
JQ2
K7-
P62
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
ID FETCH-LOGICAL-c410t-893c4d0c17ba52cf4d98789e6f61ae62a14e866c3b5ef7d58e80c9a22a54e78e3
IEDL.DBID K7-
ISICitedReferencesCount 17
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000558143000001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2153-182X
IngestDate Fri Nov 07 23:33:22 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c410t-893c4d0c17ba52cf4d98789e6f61ae62a14e866c3b5ef7d58e80c9a22a54e78e3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
PQID 2918688026
PQPubID 6623301
PageCount 11
ParticipantIDs proquest_journals_2918688026
PublicationCentury 2000
PublicationDate 2021-02-01
PublicationDateYYYYMMDD 2021-02-01
PublicationDate_xml – month: 02
  year: 2021
  text: 2021-02-01
  day: 01
PublicationDecade 2020
PublicationPlace Beijing
PublicationPlace_xml – name: Beijing
PublicationTitle Machine intelligence research (Print)
PublicationYear 2021
Publisher Springer Nature B.V
Publisher_xml – name: Springer Nature B.V
SSID ssj0003320693
Score 2.2996874
Snippet It is necessary to rely on the rail gauge to determine whether the object beside the track will affect train operation safety or not. A convenient and fast...
SourceID proquest
SourceType Aggregation Database
StartPage 85
SubjectTerms Accuracy
Algorithms
Approximation
Automation
Cameras
Curve fitting
Least squares
Mathematical models
Real time
Robustness (mathematics)
Segments
Title Rail Detection Based on LSD and the Least Square Curve Fitting
URI https://www.proquest.com/docview/2918688026
Volume 18
WOSCitedRecordID wos000558143000001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVPQU
  databaseName: Advanced Technologies & Aerospace Database
  customDbUrl:
  eissn: 2153-1838
  dateEnd: 20241214
  omitProxy: false
  ssIdentifier: ssj0003320693
  issn: 2153-182X
  databaseCode: P5Z
  dateStart: 20041001
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/hightechjournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: AUTh Library subscriptions: ProQuest Central
  customDbUrl:
  eissn: 2153-1838
  dateEnd: 20241214
  omitProxy: false
  ssIdentifier: ssj0003320693
  issn: 2153-182X
  databaseCode: BENPR
  dateStart: 20041001
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 2153-1838
  dateEnd: 20241214
  omitProxy: false
  ssIdentifier: ssj0003320693
  issn: 2153-182X
  databaseCode: K7-
  dateStart: 20041001
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LSwMxEA7aevDiAxUfteTgNbhJNo-9KPaFh1JKq1C8lGwyhYJsbbvt7zeJWz0IXrwsgb2EZPjmm5kvMwjdGRWA0VjijMh8gJJqkkuhCAPl2QMwpV286b4aDPRkkg2rhNu6klXuMDECtVvYkCO_Z1lo7K59yPD4sSRhalSorlYjNPZRnTIPwqEoq8h3joVzlsjYd9c7Nk48lZ7sCpvx9ZznIqGIGeQJqY-kfsFx9DG94__u7gQdVewSP32Zwynag-IMPYzM_B13oIyqqwK3vONy2C_64w42hcOeA-J-mOGDx0tvMYDbm9UWcG8eNdHn6LXXfWk_k2psArEpTUriGYhNXWKpyo1gdpa6TCudgZxJakAyQ1PQUlqeC5gpJzToxGaGMSNSUBr4BaoViwIuEVaOz6Sw1DkautxoLZOcOpUIx7nVRl-hxu44ppXtr6c_Z3H99-8bdMiCQiRqoBuoVq42cIsO7Lacr1dNVG91B8NRM16p_w7F2yfbTqaz
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LSwMxEB5qFfTiAxUfVXPQ4-Ju3ntQsa3F0rWUtkJvNU1SKMiqbVX8U_5Gk21XD4K3HrwFFsIyM5lvJvNlBuBUCe8YlQ6MYrFLUKgMBpyJAFvhogeLhTSZphPRbMpeL24V4DN_C-NplblPzBy1edL-jvwcx76xu3Qpw9XzS-CnRvnqaj5CY2YWDfvx7lK2yUW96vR7hnHtplu5DeZTBQJNo3AaOIDW1IQ6EgPFsB5S49JuGVs-5JGyHKuIWsm5JgNmh8IwaWWoY4WxYtQKaYnbdwmWKaGcFWG5fNNstb9vdQjBIc86_TooJYEL3nt5KTV7r-eiH1829YQI6nK3XwCQoVpt47_JYxPW5_Ezup4Z_BYUbLoNl201ekRVO814ZSkqO2g2yC2SThWp1CAX5aLETylCnRd3JiyqvI7fLKqNMtb3Dtwv5Jd3oZg-pXYPkDBkyJmOjIl8Hx8peTiIjAiZIURLJfehlIu_Pz_dk_6P7A_-_nwCq7fdu6Sf1JuNQ1jDng-TMb5LUJyOX-0RrOi36WgyPp4bEoKHRevqC-miAzs
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=article&rft.atitle=Rail+Detection+Based+on+LSD+and+the+Least+Square+Curve+Fitting&rft.jtitle=Machine+intelligence+research+%28Print%29&rft.au=Zheng%2C+Yun-Shui&rft.au=Jin%2C+Yan-Wei&rft.au=Dong%2C+Yu&rft.date=2021-02-01&rft.pub=Springer+Nature+B.V&rft.issn=2153-182X&rft.eissn=2153-1838&rft.volume=18&rft.issue=1&rft.spage=85&rft.epage=95&rft_id=info:doi/10.1007%2Fs11633-020-1241-4
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2153-182X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2153-182X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2153-182X&client=summon