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A new stopping criterion for the mean shift iterative algorithm. Its use in image segmentation
The mean shift iterative algorithm (MSHi) was proposed in 2006 , where the entropy was used as a stopping criterion. This algorithm was employed to carry out image segmentation. From then on, a theoretical base has been developed and a group of applications has been carried out using this algorithm. This paper proposes a new stopping criterion for the MSHi, where a stopping threshold via entropy is now used in another way. Many segmentation experiments were carried out by utilizing standard images. It was verified that a better segmentation was reached and that the algorithm has a better stability. An analysis on the convergence through a theorem with the new stopping criterion was carried out. A quantitative and qualitative analysis was also carried out. The goal of this paper is to compare the new stopping criterion with the old criterion. For this reason, the obtained results were not compared with other segmentation approaches, since these comparisons were previously carried out by using the old criterion in another work .
Segmentation, entropy, mean shift filtering, mean shift iterative algorithm.
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