Rough surface estimation using the Kirchhoff model

Authors:
Hossein Ragheb;Edwin R. Hancock
Affiliations:
Department of Computer Science, University of York, York, UK;Department of Computer Science, University of York, York, UK
Venue:
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Year:
2003

Citing 5
Cited 0

Surface Reflection: Physical and Geometrical Perspectives

IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Diffuse Reflection Models for Computer Vision

International Journal of Computer Vision
The Effect of Illuminant Rotation on Texture Filters: Lissajous's Ellipses

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Histogram Model for 3D Textures

CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Correlation Model for 3D Texture

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, we exploit the theory of light scattering from rough surfaces to estimate surface characteristics through reflectance measurements. Here, we analyse the Beckmann formulation of the Kirchhoff theory. We then suggest two classes of surfaces for which the appropriate techniques can be used for estimating the surface roughness, the correlation length and the surface slope. Finally, we show how the Beckmann model can be fitted to reflectance data for materials with veryrough surfaces. Since the Kirchhoff theory is inadequate for large angles of incidence, we make use of a modification to the Beckmann model. The proposed techniques have significant potential in computer vision for texture model acquisition and realistic reflectance modelling.