We generalize here the use of the 1D Boolean model for the analysis of grey level textures. Each grey image is first split into eight binary images using different criteria. Each of these binary images is separately analysed with the help of the 1D Boolean model and features are extracted from it. The final grey texture recognition is performed on the basis of these features using several classification criteria. Experiments have been carried out using an image database of 30 grey level textures, all of them with 512 × 512 pixels in size, obtaining correct classification rates between 95% and 100%, according to the classification criterion used.
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition