Based on Digital Image Lane Edge Detection and Tracking under Structure Environment for Autonomous Vehicle

Author

Feng, You ; Rong-ben, Wang ; Rong-hui, Zhang

Author_Institution

South China Univ. of Technol., Guangzhou

fYear

2007

fDate

18-21 Aug. 2007

Firstpage

1310

Lastpage

1314

Abstract

Preprocess the lane gray image to obtain binary image by using median filtering, Sobel edge detection operator and image segmentation algorithm based on maximum entropy. Propose an improved Hough transformation algorithm to obtain the feature parameter of the road edge in the binary image. Establish the area of interest (AOI) of the road edge, according to the prediction result of the Kalman filtering; adjust the size of AOI dynamically in order to track the road edge accurately. Experiments show that this algorithm is reliable and effective.

Keywords

Hough transforms; computer vision; edge detection; feature extraction; image segmentation; maximum entropy methods; median filters; road vehicles; traffic engineering computing; Hough transformation; Sobel edge detection operator; autonomous vehicle; binary image; digital image lane edge detection; feature parameter; image segmentation; lane gray image; lane tracking; maximum entropy; median filtering; road edge; structure environment; Digital filters; Digital images; Filtering; Image edge detection; Image segmentation; Kalman filters; Mobile robots; Pixel; Remotely operated vehicles; Roads; AOI; Digital image; Kalman filter; Lane edge detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2007 IEEE International Conference on

Conference_Location

Jinan

Print_ISBN

978-1-4244-1531-1

Type

conf

DOI

10.1109/ICAL.2007.4338772

Filename

4338772