High speed road boundary detection on the images for autonomous vehicle with the multi-layer CNN

Hyongsuk Kim, Seungwan Hong, Hongrak Son, Tamás Roska, Frank Werblin

Research output: Contribution to journalConference article

10 Citations (Scopus)

Abstract

A multi-layer CNN-based algorithm to find the most likely road boundaries on camera images is proposed for the possible application to autonomous vehicle driving. In the previous study, the Dynamic Programming (DP) is shown to be implemented with the multi-layer CNN. If the road-edge images are treated as the space variant distance weights, the optimal path finding algorithm of CNN-based DP can detect the optimal road boundary. Partly disconnected boundary line segments of roads could be linked by way of the most likely road boundary line segments. Fast processing speed is another advantage of the proposed CNN-based structure if it is implemented with hardware circuits. Simulation results about various different road images are included.

Original languageEnglish
Pages (from-to)V769-V772
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume5
Publication statusPublished - Jul 14 2003
EventProceedings of the 2003 IEEE International Symposium on Circuits and Systems - Bangkok, Thailand
Duration: May 25 2003May 28 2003

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'High speed road boundary detection on the images for autonomous vehicle with the multi-layer CNN'. Together they form a unique fingerprint.

  • Cite this