title: Correlated Percolation, Fractal Structures, and Scale-Invariant Distribution of Clusters in Natural Images.
abstract: Natural images are scale invariant with structures at all length scales.We formulated a geometric view of scale invariance in natural images using percolation theory, which describes the behavior of connected clusters on graphs.We map images to the percolation model by defining clusters on a binary representation for images. We show that critical percolating structures emerge in natural images and study their scaling properties by identifying fractal dimensions and exponents for the scale-invariant distributions of clusters. This formulation leads to a method for identifying clusters in images from underlying structures as a starting point for image segmentation.
authors.forename: Saeed
authors.initials: S
authors.lastname: Saremi
authors.forename: Terrence J
authors.initials: TJ
authors.lastname: Sejnowski
mesh_terms: D016000:Cluster Analysis; D017709:Fractals; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical