Recursive orientation estimation based on hypersurface reconstruction

Estimating the local orientations of a directional structure may prove to be complicated especially for complex geometries for which conventional methods, including those based on the gradient, are unsuitable. In this paper, we propose a recursive method of orientation estimation based on the reconstruction of hypersurfaces and the definition of a model of the structure in these so-called complex areas. The estimation proves to be more accurate when executed on the flattened data and driven to the initial referential. This process recursively leads to a more accurate orientation field estimation. When applied to synthetic data, the method reduces significantly the estimation bias. For real directional textures, the resulting orientation field coincides better with the perceptual orientation of the directional structures.