3D scene modelling by sinusoid encoded illumination
Document Type
Article
Publication Date
1-1-1993
Abstract
A depth estimation algorithm is proposed in this paper. In the algorithm, the sinusoidally-encoded image is used to estimate the depth by decoding the signal's propagating phase. It is based on the assumption that a planar surface should have a constant first derivative on the propagating phase. Since the major operation is differentiating, this method is highly sensitive to the noise disturbance of measurements. Random noise can be induced by the imaging channel, by unstable lighting, or by the roughness of the working environment. To subdue the influence of induced the noise a reinforced k-gradient operation is alternatively used. The algorithm is then applied to the synthetic images containing various amounts of noise to test its performance. Experimental results indicate that the estimated depth error is kept within 2% when k is greater than or equal to 6 - even when a Gaussian noise with standard deviation up to 1.5 is applied. © 1993.
Identifier
38249002636 (Scopus)
Publication Title
Image and Vision Computing
External Full Text Location
https://doi.org/10.1016/0262-8856(93)90001-W
ISSN
02628856
First Page
251
Last Page
256
Issue
5
Volume
11
Recommended Citation
Hung, DC Douglas, "3D scene modelling by sinusoid encoded illumination" (1993). Faculty Publications. 17107.
https://digitalcommons.njit.edu/fac_pubs/17107
