A nonlinear Markov random field (MRF) model-based segmentation method that uses multiscale MRF representations is developed. The proposed method labels the surface boundaries at a variety of spatial scales while labeling the surfaces, therefore it merges the advantages of region-based and edge-based segmentation approaches. The scheme is capable of fusing boundary information obtained at multiple scales simultaneously, resulting in a robust segmentation of range and intensity images.<>
Segmentation of range and intensity images using multiscale Markov random field representations
Proceedings of 1st International Conference on Image Processing ; 2 ; 187-191 vol.2
1994-01-01
586474 byte
Conference paper
Electronic Resource
English
Segmentation of Range and Intensity Images Using Multiscale Markov Random Field Representations
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