Fusing ladar and color image for detection grass off-road scenario

Author

Da-xue, Liu ; Tao, Wu ; Bin, Dai

Author_Institution

Nat. Univ. of Defense Technol., Changsha

fYear

2007

fDate

13-15 Dec. 2007

Firstpage

1

Lastpage

4

Abstract

It is necessary to extend the intelligent vehicle to navigate from structured environment to rough terrain, which is a great challenge for environment modeling. Ladar and camera are the most widely used sensors, but each of them has shortcoming. In this paper, SVM method is used to fuse the information from ladar and color camera. After registration, ladar point is represented by its position and neighbored pixels in the image. The height of the object as well as the H and S components of the color of the pixels are selected to represent the terrain. Grass and non-grass terrain are recognized based on the features. Experiment shows this method is simple and efficiency.

Keywords

automated highways; feature extraction; image colour analysis; image fusion; image recognition; image registration; image representation; optical radar; radar imaging; support vector machines; traffic engineering computing; video cameras; LADAR; SVM method; color image fusion; environment modeling; image registration; intelligent vehicle navigation; off-road scenario detection; terrain feature recognition; terrain representation; video camera; Cameras; Color; Data mining; Frequency; Laser radar; Pixel; Roads; Robot vision systems; Stereo vision; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Electronics and Safety, 2007. ICVES. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1265-5

Electronic_ISBN

978-1-4244-1266-2

Type

conf

DOI

10.1109/ICVES.2007.4456396

Filename

4456396