DocumentCode :
3052748
Title :
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
Link To Document :
بازگشت