Rectilinear structure extraction in textured images with an irregular, graph-based Markov random field model
This paper presents the application of Markov random field modelling to the extraction of poorly contrasted linear structures in textured areas. After a line feature detection step is performed, a set of straight line segments is derived from the feature image. This set of segments constitutes an irregular lattice which reproduces the image rectilinear pattern with accuracy. A Markov random field is then defined on this lattice, in order to group the sites that belong to the same structure. Finally the Markovian segmentation can be post-processed in order to extract global patterns. Results are given on pavement distress images.