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基于蚁群算法的图像分割

于 2023-07-04 发布 文件大小:2.44 kB
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抽象-分割是根据大小、 颜色、 纹理、 强度、 区域、 灰度级图像的分裂的过程。有几种算法的图像分割,但这些只是一般的图像,不像磁共振图像 (MRI) 的医疗图像。在医学领域中它是很难分析脑 MRI 图像,所以该图像的分割方法是非常重要的所以在本白皮书中我们实施了一种新的蚂蚁蚁群优化算法 (ACO) 算法 MRI Image 分割。通过使用蚁群优化算法我们获得更准确的结果相比其他分割算法的 MRI 图像。这种算法遵循用于获取他们的食物蚂蚁的实际工作。搜索食物后蚂蚁使用最短路径到巢从使用信息素痕迹的食物。信息素是一种存放于蚂蚁作为他们旅行和它蒸发一段时间后所以哪个路径有更多的信息素的化学物质这条道路是最短路径,因为许多蚂蚁从该路径只去了,这一概念用在蚁群优化算法。在本文中我们讨论了关于在 Matlab 中此算法的实现。我们比较我们拟议的算法类似进化算法的性能。这种算法跨不同的 MRI 图像集进行测试并显示高速度和准确性。

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