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环绕数约束轮廓检测。

Winding number constrained contour detection.

出版信息

IEEE Trans Image Process. 2015 Jan;24(1):68-79. doi: 10.1109/TIP.2014.2372636. Epub 2014 Nov 20.

Abstract

Salient contour detection can benefit from the integration of both contour cues and region cues. However, this task is difficult due to different nature of region representations and contour representations. To solve this problem, this paper proposes an energy minimization framework based on winding number constraints. In this framework, both region cues, such as color/texture homogeneity, and contour cues, such as local contrast and continuity, are represented in a joint objective function, which has both region and contour labels. The key problem is how to design constraints that ensure the topological consistency of the two kinds of labels. Our technique is based on the topological concept of winding number. Using a fast method for winding number computation, a small number of linear constraints are derived to ensure label consistency. Our method is instantiated by ratio-based energy functions. By successfully integrating both region and contour cues, our method shows advantages over competitive methods. Our method is extended to incorporate user interaction, which leads to further improvements.

摘要

显著轮廓检测可以受益于轮廓线索和区域线索的整合。然而,由于区域表示和轮廓表示的不同性质,这项任务很困难。为了解决这个问题,本文提出了一种基于匝数约束的能量最小化框架。在这个框架中,区域线索,如颜色/纹理均匀性,和轮廓线索,如局部对比度和连续性,都在一个联合目标函数中表示,该函数具有区域和轮廓标签。关键问题是如何设计约束条件,以确保两种标签的拓扑一致性。我们的技术基于匝数的拓扑概念。使用快速的匝数计算方法,导出了少量的线性约束条件来确保标签的一致性。我们的方法由基于比率的能量函数实例化。通过成功地整合区域和轮廓线索,我们的方法优于竞争方法。我们的方法扩展到包含用户交互,这导致了进一步的改进。

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