TY - JOUR
T1 - Use of Boolean model for texture analysis of grey images
AU - García, P.
AU - Petrou, M.
AU - Kamata, S.
N1 - Funding Information:
This work was partly supported by a British Council grant and partly by Grants P1B96-13 (Fundació Caixa-Castelló) and AGF95-0712-C03-01 (Spanish CICYT), which are gratefully acknowledged.
PY - 1999/6/10
Y1 - 1999/6/10
N2 - 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.
AB - 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.
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U2 - 10.1006/cviu.1999.0760
DO - 10.1006/cviu.1999.0760
M3 - Article
AN - SCOPUS:0033149038
SN - 1077-3142
VL - 74
SP - 227
EP - 235
JO - Computer Vision and Image Understanding
JF - Computer Vision and Image Understanding
IS - 3
ER -