Title :
Texture segmentation using zero crossings information
Author :
Smith, Guy ; Longstaff, Dennis
Author_Institution :
Co-operative Res. Centre for Sensor, Signal & Inf. Process., Queensland Univ., Australia
Abstract :
Image texture can be defined as a local two-dimensional random field. The Gauss Markov random field (GMRF) and grey level co-occurrence (GLC) algorithms compute features from models of this random field. However, the GMRF and GLC algorithms capture only second-order interactions between pixels. We describe an algorithm which models texture as a local two-dimensional random field and captures high-order interactions
Keywords :
Markov processes; image coding; image segmentation; image texture; quantisation (signal); random processes; 2D random field; Gauss Markov random field; grey level cooccurrence; high-order interactions; image coding; image segmentation; image texture; quantisation; zero crossings; Convolution; Filtering theory; Histograms; Image segmentation; Image sensors; Image texture; Lab-on-a-chip; Laplace equations; Quantization; Shape;
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-8186-8512-3
DOI :
10.1109/ICPR.1998.711131
