"Implementação paralela da transformada de distância euclidiana exata"

Abstract

The Euclidean distance transform is the operation that converts a binary image made of object and background pixels into another image, the Euclidean distance map, where each pixel has a value corresponding to the Euclidean distance from this pixel to the background. The Euclidean distance transform has important uses in computer vision, image analysis and robotics, but it is time-consuming, mainly when processing 3-D images. In this work two types of parallel computers are used to speed up the Euclidean distance transform, (i) symmetric multiprocessors (SMPs) and (ii) clusters of workstations. Two algorithms are parallelized. The first one, an independent line-column Euclidean distance transform algorithm, is parallelized on a SMP, and on a cluster. The second one, an ordered propagation Euclidean distance transform algorithm, is paralellized on a cluster.

Estudo de técnicas para separação de objetos agrupados em imagens digitais 2D

“…Sendo assim, segundo (TORELLI, 2005), é chamado 'objeto', O, o conjunto de pontos com valor 1. Tal conjunto pode ser conexo ou não.…”