Introduction - If you have any usage issues, please Google them yourself
This paper addresses the problem of segmenting an image into regions. We define a predicate for
measuring the evidence for a boundary between two regions using a graph-based representation of the image. We
then develop an efficient segmentation algorithm based on this predicate, and show that although this algorithm
makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image
segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results
with both real and synthetic images. The algorithm runs in time nearly linear in the number of graph edges and
is also fast in practice. An important characteristic of the method is its ability to preserve detail in low-variability
image regions while ignoring detail in high-variability regions