Building and Applying of 2.5D Range Image Based on Data Fusion

Author

Yuan, Xia ; Zhao, Chuan-xia

Author_Institution

Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China

fYear

2009

fDate

4-6 Nov. 2009

Firstpage

1

Lastpage

5

Abstract

Propose an algorithm to detect road area in front of the robot based on 2.5D range image to satisfy the robot to find passable road lies 20-80 m in front of it. The algorithm builds a 2.5D range image by calibrating ladar and camera. Then, it clusters points in single ladar frame using KNN. Geometrical and color information were used to segment the range image and then road area was abstracted. The experiment show the algorithm can works in semi-structural environment and has ability to deal with shadow image and ladar noise.

Keywords

calibration; cameras; computational geometry; image colour analysis; image segmentation; mobile robots; object detection; pattern clustering; robot vision; sensor fusion; camera calibration; color information; data fusion; geometrical information; image segmentation; k-nearest neighbor; road area detection; robot; single ladar frame clustering; Cameras; Clustering algorithms; Colored noise; Computer science; Image segmentation; Laser radar; Roads; Robot vision systems; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2009. CCPR 2009. Chinese Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4199-0

Type

conf

DOI

10.1109/CCPR.2009.5344114

Filename

5344114