CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1985 vol.7 Issue No.02 - February
Issue No.02 - February (1985 vol.7)
Russ Miller , Department of Mathematical Sciences, State University of New York, Binghamton, NY 13901.
Quentin F. Stout , Department of Mathematical Sciences, State University of New York, Binghamton, NY 13901; Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbo
Although mesh-connected computers are used almost exclusively for low-level local image processing, they are also suitable for higher level image processing tasks. We illustrate this by presenting new optimal (in the O-notational sense) algorithms for computing several geometric properties of figures. For example, given a black/white picture stored one pixel per processing element in an n Ã? n mesh-connected computer, we give ¿(n) time algorithms for determining the extreme points of the convex hull of each component, for deciding if the convex hull of each component contains pixels that are not members of the component, for deciding if two sets of processors are linearly separable, for deciding if each component is convex, for determining the distance to the nearest neighboring component of each component, for determining internal distances in each component, for counting and marking minimal internal paths in each component, for computing the external diameter of each component, for solving the largest empty circle problem, for determining internal diameters of components without holes, and for solving the all-points farthest point problem. Previous mesh-connected computer algorithms for these problems were either nonexistent or had worst case times of ¿(n2). Since any serial computer has a best case time of ¿(n2) when processing an n Ã? n image, our algorithms show that the mesh-connected computer provides significantly better solutions to these problems.
Russ Miller, Quentin F. Stout, "Geometric Algorithms for Digitized Pictures on a Mesh-Connected Computer", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.7, no. 2, pp. 216-228, February 1985, doi:10.1109/TPAMI.1985.4767645