A new approach for image segmentation for scenes that contain distinct
objects is presented. A sequence of graphs N-s(t) is defined, where N
-s(t) is the number of connected objects composed of at least s pixels
, for the image thresholded at t. The sequence of graphs is built in a
lmost linear time complexity, namely at O(alpha(n, n). n), where alpha
(n, n) is the inverse of the Ackermann function, and n is the number o
f pixels in the image. Stable states on the graph in the appropriate '
'resolution'' s correspond to threshold values that yield a segmentat
ion similar to a human observer. The relevance of a Percolation model
to the graphs N-s(t) is discussed.