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Interactive image segmentation by improved maximal similarity based region merging

机译:通过改进基于最大相似性的区域合并的交互式图像分割

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In medical image processing, interactive image segmentation is an important part, because it can obtain accurate segment results with less human effort compared with manual scribing. We proposed an improved algorithm of maximal similarity based region merging, compared with the algorithm proposed in [3], our algorithm use SLIC superpixels segmentation to obtain presegmented regions, using SLIC superpixles, it is easy to control the number of presegmentation regions. We also introduce the texture features differeces while rigion merging, so we can obtain the accuracy of similarity measurement. Experimental results show that our algorithm can obtain comparable results.
机译:在医学图像处理中,交互式图像分割是一个重要的部分,因为它可以通过手动划线比较较少的人力努力获得准确的细分导致。我们提出了一种改进的最大相似性基于区域合并的算法,与[3]中提出的算法相比,我们的算法使用SLIC Superpixels分段来获得PreseDimoned地区,使用Slic Superpixles,很容易控制PRESE分段区域的数量。我们还介绍了Region合并的纹理特征,因此我们可以获得相似度测量的准确性。实验结果表明,我们的算法可以获得可比结果。

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