Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation using 2-D Gabor Elementary Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of Texture Features Based on Gabor Filters
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Identifying and Locating Surface Defects in Wood: Part of an Automated Lumber Processing System
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multiscale representation including opponent color features for texture recognition
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
A common issue in many computer vision applications is the effect of the illumination conditions on the performance and reliability of the built system. In many cases the researchers have to face an extra problem: to study the environmental conditions of the facilities where the application will run, the light technology and the wattage of the chosen lamps, nowadays we are moving to LED technology due to the increased life and absence of flicker, among other benefits. Nevertheless, it would be desirable to make the intelligent system more robust to lighting conditions changes, as in the case of texture classification systems [1]. On such systems the effect of light changes on the measured features may eventually lead to texture misclassification and performance degradation. In this paper we present an approach that will be helpful to overcome such problems when the light comes from a directional source, such as halogen projectors, LED arrays, etc.