A fuzzy vehicle detection based on contour size similarity

Bing-Fei Wu*, Chuan Tsai Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In this paper, the obstacle detection for autonomous vehicle is carried out by a monocular camera, which is capable of detecting multiple obstacles, identifying the difference between obstacles and text or shadows on the road surface The task of detection can be fulfilled under the circumstances of general brightness or in the presence of strong sunshine. An obstacle detection approach named Contour Size Similarity (CSS) is developed in this paper. CSS is a way to make use of the contour size of objects and compare the similarity between objects and obstacles detected by means of fuzzy so as to judge whether the objects in the images are the obstacles we want to detect. The obstacles in this paper mainly refer to vehicles. Vehicles and obstacles with similar contour of vehicles can be detected by CSS. Then, we use section division to find out the nearest obstacle in separate section to provide necessary information for autonomous vehicles.

Original languageEnglish
Title of host publication2005 IEEE Intelligent Vehicles Symposium, Proceedings
Pages496-501
Number of pages6
DOIs
StatePublished - 6 Jul 2005
Event2005 IEEE Intelligent Vehicles Symposium - Las Vegas, NV, United States
Duration: 6 Jun 20058 Jun 2005

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2005

Conference

Conference2005 IEEE Intelligent Vehicles Symposium
CountryUnited States
CityLas Vegas, NV
Period6/06/058/06/05

Keywords

  • Autonomous vehicles
  • Image
  • Obstacle detection
  • Vision-based

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