Abstract

The signed Euclidean distance transform is a modified version of Danielsson’s Euclidean distance transform [1]. This distance transform produces a distance map in which each pixel is a vector of two integer components. If a distance map is created inside the objects, the two integer values of a pixel in the distance map represent the displacements of the pixel from the nearest background point in x and y directions, respectively. The unique feature of this distance transform that a vector in the distance map is always pointing to the nearest background point is exploited in several applications, such as the detection of dominant points in digital curves, curve smoothing, computing Dirichlet tessellations and finding convex hulls.

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