An improved seeded region growing algorithm
Artikel i vetenskaplig tidskrift, 1997

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

watershed segmentation

priority queue


seeded region growing


Andrew Mehnert

Chalmers, Signaler och system

P. Jackway

Pattern Recognition Letters

0167-8655 (ISSN)

Vol. 18 10 1065-1071


Livsvetenskaper och teknik (2010-2018)


Datorseende och robotik (autonoma system)

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