  This paper presents an efficient automatic color image segmentation method
using a seeded region growing and merging method based on square elemental
regions. Our segmentation method consists of the three steps: generating seed
regions, merging the regions, and applying a pixel-wise boundary determination
algorithm to the resultant polygonal regions. The major features of our method
are as follows: the use of square elemental regions instead of pixels as the
processing unit, a seed generation method based on enhanced gradient values, a
seed region growing method exploiting local gradient values, a region merging
method using a similarity measure including a homogeneity distance based on
Tsallis entropy, and a termination condition of region merging using an
estimated desired number of regions. Using square regions as the processing
unit substantially reduces the time complexity of the algorithm and makes the
performance stable. The experimental results show that our method exhibits
stable performance for a variety of natural images, including heavily textured
areas, and produces good segmentation results using the same parameter values.
The results of our method are fairly comparable to, and in some respects better
than, those of existing algorithms.
