A new minimum variance region growing algorithm for image segmentation

doi:10.1016/S0167-8655(97)00012-3

A new minimum variance region growing algorithm for image segmentation

1997-03-01

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DOI：10.1016/S0167-8655(97)00012-3

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Region growing is a very useful technique for image segmentation. Its efficiency mainly depends on its aggregation criterion. In the present paper, a new algorithm is proposed with a homogeneity criterion based on an adequate tuning between spatial neighbourhood and histogram neighbourhood. It differs from other techniques by reconsidering the pixel (or voxel) assignments on each step by a process which minimizes variance through special dilations. Thus, the region created by an initial seed can be non-connected and possibly does not contain this seed. Examples are given in dental surgery for 2D X-Ray images (and their associated 3D block) and for 3D images acquired by the Morphometre, the new 3D scanner constructed by GEMSE (General Electric Medical Systems). (C) 1997 Published by Elsevier Science B.V.

Keywords:

image segmentation

region growing

variance minimization

homogeneity

histogram

morphological operations

A new minimum variance region growing algorithm for image segmentation

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