| 한글제목(Korean Title) |
Lane Detection and Tracking Using Classification in Image Sequences |
| 영문제목(English Title) |
Lane Detection and Tracking Using Classification in Image Sequences |
| 저자(Author) |
Sungsoo Lim
Daeho Lee
Youngtae Park
|
| 원문수록처(Citation) |
VOL 08 NO. 12 PP. 4489 ~ 4501 (2014. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.
|
| 키워드(Keyword) |
Lane detection
advanced driver assistance system
feature extraction
machine vision
intelligent transportation system
|
| 파일첨부 |
PDF 다운로드
|
