Irregular tessellation based image analysis

Abstract

Independent stochastic processes are used to generate in parallel irregular tessellations of an image. Recursive application of the procedure yields a multiresolution hierarchy adapted to the content of the image. The hierarchy is similar to traditional image pyramids: its height is of log (image size) order, but by being adapted to the input, it eliminates the artifacts frequently present in the latter. The output obtained at the apex of the hierarchy can be used for fast image analysis. The technique was applied to connected component labeling (labeled images) and segmentation (gray-level images).<>