Texture segmentation through salient texture patches
Lech Szumilas, Allan Hanbury · 2006
A novel approach to automatic, hierarchical texture detection in single images as a step towards image understanding is presented. First, the proposed method searches for alternating color patterns through hierarchical clustering of color pairs from adjacent, symmetrical image segments to localize salient regions in terms of color and texture. Second, the salient regions are fed as seeds to an image segmentation method based on min-cut/max-flow in the graph to localize the texture boundaries more accurately. The final result is a hierarchy of potential textured regions in the image useful for further object/texture recognition step. This work gives a proof of concept that the stable salient texture regions supported by a semi-automatic segmentation algorithm may provide fully automatic image segmentation into uniform color and/or texture regions. The results are presented on some images of natural scenes from the Berkeley database.