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An improved seeded region growing algorithm

delete1997-10-01
delete261
PRE
AI
A
Andrew Mehnert *
P
Paul Jackway
DOI:10.1016/S0167-8655(97)00131-1delete
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摘要

摘要

En 中文
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.
Keyword:
priority queue
seeded region growing
segmentation
watershed segmentation
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Pattern Recognition Letters 封面图
Pattern Recognition Letters
IF:
3.3
论文数:
8.0K
被引数:
1.6W

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