Texture Measures for Automatic Classification of Pulmonary Disease
IEEE Transactions on Computers
Edge and Curve Detection: Further Experiments
IEEE Transactions on Computers
Grating Cell Operator Features for Oriented Texture Segmentation
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Automated lesion detection in retinal images
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Hi-index | 14.98 |
A new technique for image texture analysis is described which uses the relative frequency of local extremes in grey level as the principal measure. This method is invariant to multiplicative gain changes (such as caused by changes in illumination level or film processing) and is invariant to image resolution and sampling rate if the image is not undersampled. The algorithm described is computationally simple and can be implemented in hardware for real-time analysis. Comparisons are made between this new method and the spatial dependence method of texture analysis using 49 samples of each of eight textures. The new method seems just as accurate and considerably faster.