Evolutionary image segmentation based on multiobjective clustering
Evolutionary image segmentation based on multiobjective clustering
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DOI：
10.1109/cec.2009.4983250
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发表时间：
2009-05
期刊：
影响因子：
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通讯作者：
S. Shirakawa;T. Nagao
中科院分区：
文献类型：
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作者：
S. Shirakawa;T. Nagao
在图像处理和识别领域中，图像分割是一项重要的基础技术，它将图像分割成多个区域（像素集）。本文提出了一种基于多目标聚类的进化图像分割方法。在该方法中，两个目标，整体偏差和边缘值，同时使用多目标进化算法进行优化。这些目标是图像分割的重要因素。所提出的方法找到各种解决方案（图像分割结果）通过使用一个进化过程。我们将所提出的方法应用于几个图像分割问题，并确认得到各种解决方案。此外，我们使用一个简单的启发式方法来选择一个解决方案，从原来的Pareto解决方案，并显示一个良好的图像分割结果被选中。
In the fields of image processing and recognition, image segmentation is an important basic technique in which an image is partitioned into multiple regions (sets of pixels). In this paper, we propose a method for evolutionary image segmentation based on multiobjective clustering. In this method, two objectives, overall deviation and edge value, are optimized simultaneously using a multiobjective evolutionary algorithm. These objectives are important factors for image segmentation. The proposed method finds various solutions (image segmentation results) by the use of an evolutionary process. We apply the proposed method to several image segmentation problems and confirm that various solutions are obtained. In addition, we use a simple heuristic method to select one solution from the original Pareto solutions and show that a good image segmentation result is selected.