Abstract
A new low-level procedure for image segmentation is described. The procedure transforms a digital picture to a matrix of square arrays which can be identified as being either homogeneous or nonhomogenous. The nonhomogeneous arrays correspond to boundaries between adjacent regions and as such they represent a first approximation to the segmentation problem. The mathematics involved are related to random walks in a plane bounded by an absorbing barrier. The probabilities connected with the differences between the expected (theoretical) and the observed frequencies of reaching disjoint segments of the boundary are the clues to distinguish a homogeneous array from a nonhomogeneous array. The procedure has been implemented and two applications are shown.
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