An Efficient Ego-Lane Detection Model to Avoid False-Positives Detection of Guardrails

Bottazzi, Vitor S.; Jo, Jun; Stantić, Bela; Borges, Paulo Vinicius Koerich

doi:10.1007/978-3-319-16841-8_67

Advances in Intelligent Systems and Computing

2015

DOI: 10.1007/978-3-319-16841-8_67

|View full text |Cite

An Efficient Ego-Lane Detection Model to Avoid False-Positives Detection of Guardrails

Vitor S. Bottazzi

Jun Jo

Bela Stantić

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Improved Ant Colony based Optimization based Lane Colorization for Curved Lane Images

Ritika¹,

Bhalla²

2015

IJCA

View full text Add to dashboard Cite

There are many researchers who have worked and are working on creating and developing many techniques in intelligent transportation systems with advanced driving assistances system which are able to ensure the safety in the roads and congested traffic conditions. The road accidents are the main causes for the sudden death in this world. Even though we have many good and advanced techniques in this world, we are left over with something to make it better than before. In this paper, a new technique for lane detection using fuzzy c means clustering and ant colony optimization has been devised. The algorithm performs very efficiently in case of the curved roads.

show abstract

Improved Ant Colony based Optimization based Lane Colorization for Curved Lane Images

Ritika¹,

Bhalla²

2015

IJCA

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

An Efficient Ego-Lane Detection Model to Avoid False-Positives Detection of Guardrails

Cited by 1 publication

References 15 publications

Improved Ant Colony based Optimization based Lane Colorization for Curved Lane Images

Improved Ant Colony based Optimization based Lane Colorization for Curved Lane Images

Contact Info

Product

Resources

About