Real-time on-road vehicle detection algorithm based on monocular vision

Xiaoyong Wang, Wang Bo, Song Lu

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

7 Citations (Scopus)

Abstract

Increasing driving safety by virtue of advanced technology requires real-time and accurate detection of vehicles in far and close distance, which pose a threat to the host vehicle. This paper presents a real-time on-road vehicle detection algorithm based on monocular vision. First, auto-adapted threshold segmentation is proposed to extract shadow features. Then, a special mask is used for morphology computing to retain the features of vehicles in far and close distance. And, vanishing point constraint is applied for the fast verification of vehicles. Finally, the tracking of vehicles assists to stabilize the detection results. The experiments show that the average processing speed reaches 39 frames/ms, and the fast detection of vehicle under different weather conditions in the day time can also work accurately.

Original languageEnglish
Title of host publicationProceedings of 2nd International Conference on Computer Science and Network Technology, ICCSNT 2012
Pages772-776
Number of pages5
DOIs
Publication statusPublished - 2012
Event2nd International Conference on Computer Science and Network Technology, ICCSNT 2012 - Changchun, China
Duration: 29 Dec 201231 Dec 2012

Publication series

NameProceedings of 2nd International Conference on Computer Science and Network Technology, ICCSNT 2012

Conference

Conference2nd International Conference on Computer Science and Network Technology, ICCSNT 2012
Country/TerritoryChina
CityChangchun
Period29/12/1231/12/12

Keywords

  • Vehicle Detection
  • morphology computing
  • threshold segmentation
  • vanishing point constraint

Fingerprint

Dive into the research topics of 'Real-time on-road vehicle detection algorithm based on monocular vision'. Together they form a unique fingerprint.

Cite this