Share Email Print
cover

Proceedings Paper

Imaging lidar based 3D terrain matching using feature vector
Author(s): Hua Cheng; Jie Ma; Junbin Gong
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A novel 3D terrain matching algorithm is presented in this paper. A terrain feature vector map (FVM), composed of local mean and local gradient, is employed to represent the terrain elevation map (TEM). Compared with traditional matching algorithm using the magnitude of gradient to match, the new algorithm uses each component of the gradient vector to match individually, and it is able to generate two interim matching positions. Different from traditional matching algorithms which usually estimate an optimum matching position under some criterions at the end, the new algorithm fused the two interim matching positions to generate a final matching position or refuse to position in order to increase the matching confidence, which is very important because it is hardly acceptable to employ a mismatched position to correct the error of Inertial Navigation System (INS). Due to the stability of terrain and the high-precision of lidar ranging, the mean of a sensed terrain elevation map (STEM) sized terrain is quite stable. So it is bestowed to accelerate the matching process and to reduce mismatches at different terrain heights. Compared with other mismatch-eliminated methods based on neural network (NN) or support vector machine (SVM), the new method do not need training samples and is more stable and robust. Experimental results show that the proposed algorithm is effective and robust.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678715 (15 November 2007); doi: 10.1117/12.749181
Show Author Affiliations
Hua Cheng, Huazhong Univ. of Science and Technology (China)
Jie Ma, Huazhong Univ. of Science and Technology (China)
Junbin Gong, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing

© SPIE. Terms of Use
Back to Top