User-steered image segmentation paradigms: Live wire and live lane
User-steered image segmentation paradigms: Live wire and live lane
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DOI：
10.1006/gmip.1998.0475
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发表时间：
1998-07-01
期刊：
影响因子：
--
通讯作者：
Lotufo, RDA
中科院分区：
文献类型：
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作者：
Falcao, AX;Udupa, JK;Lotufo, RDA
在多维图像分析中，存在并将继续存在自动图像分割方法失败的情况，在此过程中需要大量的用户帮助。针对这种情况的分段研究的主要目标应该是（i）在执行分段过程时为用户提供有效的控制，以及（ii）最大限度地减少用户在该过程中所需的总时间。考虑到这些目标，我们在本文中提出了两种范例，称为带电线路和带电通道，用于大型应用中的实际图像分割。对于这两种方法，我们将像素顶点和定向边视为形成图，为每个定向边分配一组特征来表征其“边界”，并将特征值转换为成本。我们提供培训设施以及自动最佳特征和变换选择方法，以便可以在任何应用中以一致的有效性进行这些分配。在带电导线中，用户首先选择边界上的初始点。对于光标指示的任何后续点，都会找到并实时显示从初始点到当前点的最佳路径。因此，用户手头上有一根带电电线，通过移动光标来移动该带电电线。如果光标靠近边界，则带电电线会捕捉到边界上。此时，如果火线适当地描述了边界，则用户将光标放置在现在成为新起点的位置，并且该过程继续。几个点（带电线段）通常足以分割整个二维边界。在实时车道中，用户仅选择初始点。当光标在边界周围的通道内移动时，会自动选择后续点，该边界的宽度随着光标运动的速度和加速度而变化。实时生成并显示连续点之间的带电线段。当用户在边界附近粗略标记时，用户会感觉到曲线捕捉到边界上。我们描述了正式的评估研究，以基于跟踪的速度和可重复性以及从大型正在进行的应用程序中获取的数据来比较新方法与手动跟踪的实用性。研究表明，从统计上看，新方法的可重复性显着提高，并且比手动追踪快 1.5-2.5 倍。 (C) 1998 年学术出版社。
In multidimensional image analysis, there are, and will continue to be, situations wherein automatic image segmentation methods fail, calling for considerable user assistance in the process. The main goals of segmentation research for such situations ought to be (i) to provide effective control to the user on the segmentation process while it is being executed, and (ii) to minimize the total user's time required in the process. With these goals in mind, we present in this paper two paradigms, referred to as live wire and live lane, for practical image segmentation in large applications. For both approaches, we think of the pixel vertices and oriented edges as forming a graph, assign a set of features to each oriented edge to characterize its "boundariness," and transform feature values to costs. We provide training facilities and automatic optimal feature and transform selection methods so that these assignments can be made with consistent effectiveness in any application. In live wire, the user first selects an initial point on the boundary. For any subsequent point indicated by the cursor, an optimal path from the initial point to the current point is found and displayed in real time. The user thus has a live wire on hand which is moved by moving the cursor, If the cursor goes close to the boundary, the live wire snaps onto the boundary. At this point, if the live wire describes the boundary appropriately, the user deposits the cursor which now becomes the new starting point and the process continues. A few points (live-wire segments) are usually adequate to segment the whole 2D boundary. in live lane, the user selects only the initial point. Subsequent points are selected automatically as the cursor is moved within a lane surrounding the boundary whose width changes as a function of the speed and acceleration of cursor motion. Live-wire segments are generated and displayed in real time between successive points. The users get the feeling that the curve snaps onto the boundary as and while they roughly mark in the vicinity of the boundary.We describe formal evaluation studies to compare the utility of the new methods with that of manual tracing based on speed and repeatability of tracing and on data taken from a large ongoing application. The studies indicate that the new methods are statistically significantly more repeatable and 1.5-2.5 times faster than manual tracing. (C) 1998 Academic Press.