Projects per year
Abstract
Illumination effects cause problems for many computer vision algorithms. We present a user-friendly interactive system for robust illumination-invariant image generation. Compared with the previous automated illumination-invariant image derivation approaches, our system enables users
to specify a particular kind of illumination variation for removal. The derivation of illumination-invariant image is guided by the user input. The input is a stroke that defines an area covering a set of pixels whose intensities are influenced predominately by the illumination variation.
This additional flexibility enhances the robustness for processing non-linearly rendered images and the images of the scenes where their illumination variations are difficult to estimate automatically. Finally, we present some evaluation results of our method.
to specify a particular kind of illumination variation for removal. The derivation of illumination-invariant image is guided by the user input. The input is a stroke that defines an area covering a set of pixels whose intensities are influenced predominately by the illumination variation.
This additional flexibility enhances the robustness for processing non-linearly rendered images and the images of the scenes where their illumination variations are difficult to estimate automatically. Finally, we present some evaluation results of our method.
Original language | English |
---|---|
Title of host publication | Color and Imaging Conference |
Publisher | Society for Imaging Science and Technology |
Pages | 186-190 |
Volume | 2015 |
Publication status | Published - 18 Oct 2015 |
Profiles
-
Graham Finlayson
- School of Computing Sciences - Professor of Computing Science
- Colour and Imaging Lab - Member
Person: Research Group Member, Academic, Teaching & Research
Projects
- 1 Finished
-
Colour space homography
Finlayson, G. & Trollope, P.
Engineering and Physical Sciences Research Council
28/02/15 → 27/02/19
Project: Research