Robust Photometric Invariant Region Detection in Multispectral Images

Authors:
Th. Gevers;H. M. G. Stokman
Affiliations:
ISIS, Informatics Institute, Faculty of Science, University of Amsterdam, The Netherlands;ISIS, Informatics Institute, Faculty of Science, University of Amsterdam, The Netherlands
Venue:
International Journal of Computer Vision
Year:
2003

Citing 9
Cited 3

A color clustering technique for image segmentation

Computer Vision, Graphics, and Image Processing
A physical approach to color image understanding

International Journal of Computer Vision
Color image segmentation with detection of highlights and local illumination induced by inter-reflections

Color
GLHS: a generalized lightness, hue, and saturation color model

CVGIP: Graphical Models and Image Processing
A novel vector-based approach to color image retrieval using a vector angular-based distance measure

Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Illumination for computer generated pictures

Communications of the ACM
Multiresolution Color Image Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram-based segmentation in a perceptually uniform color space

IEEE Transactions on Image Processing
PicToSeek: combining color and shape invariant features for image retrieval

IEEE Transactions on Image Processing

On the use of the overlapping area matrix for image segmentation evaluation: A survey and new performance measures

Pattern Recognition Letters
On the use of the overlapping area matrix for image segmentation evaluation: a survey and new performance measures

Pattern Recognition Letters
Estimation of intensity uncertainties for computer vision applications

ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Our aim is to detect photometric invariant regions in multispectral images robust against sensor noise. Therefore, different polar angle representations of a spectrum are examined for invariance using the dichromatic reflection model. These invariant representations take advantage of white balancing. Based on the camera sensitivity, a theoretical expression is obtained of the certainty associated with the polar angular representations under the influence of noise. The expression is employed by the segmentation technique to ensure robustness against sensor noise.