Integrating region growing and edge detection
Pavlidis, T.
Liow, Y.-T.
State Univ. of New York, Stony Brook, NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 1990
Volume: 12,
Issue: 3
On page(s): 225-233
ISSN: 0162-8828
References Cited: 24
CODEN: ITPIDJ
INSPEC Accession Number: 3641637
Digital Object Identifier: 10.1109/34.49050
Current Version Published: 2002-08-06
Abstract
A method that combines region growing and edge detection for image
segmentation is presented. The authors start with a split-and merge
algorithm wherein the parameters have been set up so that an
over-segmented image results. Region boundaries are then eliminated or
modified on the basis of criteria that integrate contrast with boundary
smoothness, variation of the image gradient along the boundary, and a
criterion that penalizes for the presence of artifacts reflecting the
data structure used during segmentation (quadtree in this case). The
algorithms were implemented in the C language on a Sun 3/160 workstation
running under the Unix operating system. Simple tool images and aerial
photographs were used to test the algorithms. The impression of human
observers is that the method is very successful on the tool images and
less so on the aerial photograph images. It is thought that the success
in the tool images is because the objects shown occupy areas of many
pixels, making it is easy to select parameters to separate signal
information from noise
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