Image segmentation is a
very important step in image processing. Extracting useful
information from an image is the goal of image segmentation.
In this paper, two
main segmentation methods (Region growing and Contour following) are tested
in order to research the advantages, disadvantages and characteristics.
Tested algorithms are four neighbor region growing algorithm, gradient
operators, histogram based thresholding, thresholding based on boundary
characteristics and Hough transform.
The performance of
each algorithm was evaluated by using real MRI images, remote sensing images
and synthetic images. The synthetic images were used to validate the algorithms
and to illustrate difficulties that are encountered with real images. The
test environment was constructed as an IDL(5)
widget (graphic user interface).
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