A Markovian model for contour grouping

Sabine Urago, J. Zerubia, M. Berthod
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引用次数: 15

Abstract

Describes an algorithm which restores images of incomplete contours using a Markovian model. In order to complete the boundaries, a criterion is defined and introduced in an energy function, which has to be optimized. A deterministic relaxation algorithm ICM ("iterated conditional mode") is implemented to minimize this energy function. It generates a configuration in which the contours are reconstructed. Several examples of real image restoration have been tested on a SIMD computer (Connection Machine CM 200). This algorithm allows one to fill up large gaps and to get a better contour grouping.
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轮廓分组的马尔可夫模型
描述一种使用马尔可夫模型恢复不完整轮廓图像的算法。为了完成边界,定义了一个准则,并在能量函数中引入该准则,对该准则进行优化。实现了一种确定性松弛算法ICM(“迭代条件模式”)来最小化该能量函数。它生成一个重构轮廓的结构。在一台SIMD计算机(连接机CM 200)上测试了几个真实图像恢复的示例。该算法可以填补较大的空白,并得到更好的轮廓分组。
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