An improved seeded region growing algorithm

Andrew Mehnert, Paul Jackway

Research output: Contribution to journalArticlepeer-review

273 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1065-1071
Number of pages7
JournalPattern Recognition Letters
Issue number10
Publication statusPublished - 1 Jan 1997
Externally publishedYes


Dive into the research topics of 'An improved seeded region growing algorithm'. Together they form a unique fingerprint.

Cite this