Interactive Segmentation with Intelligent Scissors

Eric N. Mortensen, William A. Barrett
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引用次数: 624

Abstract

We present a new, interactive tool calledIntelligent Scissorswhich we use for image segmentation. Fully automated segmentation is an unsolved problem, while manual tracing is inaccurate and laboriously unacceptable. However, Intelligent Scissors allow objects within digital images to be extracted quickly and accurately using simple gesture motions with a mouse. When the gestured mouse position comes in proximity to an object edge, alive-wire boundary“snaps” to, and wraps around the object of interest. Live-wire boundary detection formulates boundary detection as an optimal path search in a weighted graph. Optimal graph searching provides mathematically piece-wise optimal boundaries while greatly reducing sensitivity to local noise or other intervening structures. Robustness is further enhanced withon-the-fly trainingwhich causes the boundary to adhere to the specific type of edge currently being followed, rather than simply the strongest edge in the neighborhood.Boundary coolingautomatically freezes unchanging segments and automates input of additional seed points. Cooling also allows the user to be much more free with the gesture path, thereby increasing the efficiency and finesse with which boundaries can be extracted.

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智能剪刀的交互式分割
我们提出了一种新的交互式工具,称为智能剪刀,用于图像分割。全自动分割是一个未解决的问题,而手工跟踪是不准确的,费力的不可接受的。然而,智能剪刀允许使用简单的鼠标手势动作快速准确地提取数字图像中的物体。当手势鼠标位置接近对象边缘时,活线边界“扣”到感兴趣的对象,并环绕该对象。Live-wire边界检测将边界检测表述为加权图中的最优路径搜索。最优图搜索提供了数学上分段的最优边界,同时大大降低了对局部噪声或其他干预结构的敏感性。鲁棒性在实时训练中进一步增强,这使得边界坚持当前所遵循的特定类型的边缘,而不仅仅是邻居中最强的边缘。边界冷却自动冻结不变的片段,并自动输入额外的种子点。冷却还允许用户更自由地使用手势路径,从而提高提取边界的效率和技巧。
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