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Novel Adaptive Balloon Active Contour Method based on internal force for image segmentation - A systematic evaluation on synthetic and real images

机译:基于内力的新型自适应气球主动轮廓线图像分割方法-对合成图像和真实图像的系统评价

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Many studies have been conducted on digital image segmentation, seeking to overcome the limitations of different methods for specific applications. Thus, existing techniques are improved and new methods created. This paper proposes a new Active Contour Method (ACM) applied to the segmentation of objects in digital images. The proposed method is called Adaptive Balloon ACM and its main contribution is the new internal Adaptive Balloon energy that minimizes the energy of each point on the curve using the topology of its neighboring points, and thus moves the curve toward the object of interest. The method can be initialized inside or outside the object of interest, and can even segment objects that have complex shapes. There are no limitations as to its startup location. This work evaluates the proposed method in several applications and compares it with other ACMs in the literature. This new method obtained superior results, especially when the objects to be segmented were tubular and had bifurcations. Thus the proposed method can be considered effective in segmenting complex shapes in digital images and gave promising results in various applications.
机译:关于数字图像分割已经进行了许多研究,试图克服针对特定应用的不同方法的局限性。因此,对现有技术进行了改进并创建了新方法。本文提出了一种新的主​​动轮廓方法(ACM),该方法应用于数字图像中的对象分割。所提出的方法称为“自适应气球ACM”,其主要贡献是新的内部“自适应气球”能量,该能量使用其相邻点的拓扑结构将曲线上每个点的能量最小化,从而将曲线移向感兴趣的对象。该方法可以在感兴趣的对象内部或外部进行初始化,甚至可以分割形状复杂的对象。其启动位置没有限制。这项工作评估了几种应用中提出的方法,并将其与文献中的其他ACM进行了比较。这种新方法获得了优异的效果,尤其是当要分割的对象是管状的并且具有分叉的对象时。因此,所提出的方法可以被认为有效地分割了数字图像中的复杂形状,并在各种应用中给出了可喜的结果。

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