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Color Image Segmentation Using Adaptive GrowCut Method

机译:使用自适应GrowCut方法进行彩色图像分割

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An adaptive algorithm for interactive multi-label segmentation of 2-dimensional color images using GrowCut has been carry out in this technique. Except certain small number of user-labelled pixels, the remainder of the image is segmented automatically by a layered automaton. This technique is iterative, since the mechanism labels the image automatically. The segmentation task is complex to compute. User can monitor the progress of segmentation and redirect the algorithm with respect to human participation. The proposed system contains two phases. During the first level the original input color image is segmented using the GrowCut method. In the following phase the resulting image is processed under color image segmentation method. In the areas, where the segmentation is dependably computed automatically no further user effort is necessary. Outcomes of segmenting standard photos and images are presented. Our experiments show that a little user effort is required for segmentation of moderately tough images.
机译:在这种技术中,已经实现了使用GrowCut进行二维彩色图像交互式多标签分割的自适应算法。除了某些少量的用户标记的像素外,其余图像会由分层自动机自动分割。此技术是迭代的,因为该机制会自动标记图像。细分任务计算起来很复杂。用户可以监视分段的进度,并针对人类参与重定向算法。拟议的系统分为两个阶段。在第一级中,使用GrowCut方法对原始输入彩色图像进行分割。在接下来的阶段中,将在彩色图像分割方法下处理所得图像。在可靠地自动计算分段的区域中,无需进一步的用户工作。提出了分割标准照片和图像的结果。我们的实验表明,对中等难度的图像进行分割需要用户付出一点努力。

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