论文标题
通过KNN图使用标签传播的简单交互式图像分割
Simple Interactive Image Segmentation using Label Propagation through kNN graphs
论文作者
论文摘要
许多交互式图像分割技术基于半监督的学习。用户可以标记每个对象的一些像素，而SSL算法将将标签从标记到未标记的像素的标签传播，从而找到对象边界。本文提出了一种新的基于SSL图的交互式图像分割方法，该方法使用未指向和未加权的KNN图，未标记的节点从中接收其他节点（标记或未标记）的贡献。它比许多其他技术更简单，但是它仍然可以在图像分割任务中实现明显的分类准确性。计算机模拟是使用从Microsoft GrabCut数据集提取的一些现实世界图像进行的。分割结果显示了拟议方法的有效性。
Many interactive image segmentation techniques are based on semi-supervised learning. The user may label some pixels from each object and the SSL algorithm will propagate the labels from the labeled to the unlabeled pixels, finding object boundaries. This paper proposes a new SSL graph-based interactive image segmentation approach, using undirected and unweighted kNN graphs, from which the unlabeled nodes receive contributions from other nodes (either labeled or unlabeled). It is simpler than many other techniques, but it still achieves significant classification accuracy in the image segmentation task. Computer simulations are performed using some real-world images, extracted from the Microsoft GrabCut dataset. The segmentation results show the effectiveness of the proposed approach.
