Abstract
This
paper focuses on the problem Image Segmentation which aims at subdividing a
given image into its constituent objects. Here an unsupervised method for color
image segmentation is proposed where we first perform a Minimum Spanning Tree
(MST) based “natural grouping” of the image pixels to find out the clusters of
the pixels having RGB values within a certain range present in the image. Then
the pixels nearest to the centers of those clusters are found out and marked as
the seeds. They are then used for region growing based image segmentation
purpose. After that a region merging based segmentation method having a suitable
threshold is performed to eliminate the effect of over segmentation that may
still persist after the region growing method. This proposed method is
unsupervised as it does not require any prior informationabout the number of
regions present in a given image. The experimental results show that the
proposed method can find homogeneous regions present in a given image
efficiently.
Keywords:
Segmentation, Region Growing, Natural
Grouping.
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