Boundary detection through dynamic polygons
Boundary detection through dynamic polygons
复制标题
通过动态多边形进行边界检测
DOI：
10.1111/1467-9868.00143
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
Peter Green
中科院分区：
文献类型：
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作者：
Antonio Pievatolo;Peter Green
提出了一种对背景上具有恒定灰度的目标的含噪二值图像进行贝叶斯复原的方法。恢复，通过拟合多边形与任何数量的边的对象的轮廓，是由一个新的概率模型，用于生成的多边形在一个紧凑的子集R2，这是用来作为一个先验分布的多边形。一些可测量性问题提出了正确的规格模型得到解决。利用可逆跳马尔可夫链蒙特卡罗方法，从先验和后验两个方面进行了模拟，并讨论了其实现方法和收敛性。给出了一个合成图像恢复的例子，并与现有的基于像素的方法进行了比较。
A method for the Bayesian restoration of noisy binary images portraying an object with constant grey level on a background is presented. The restoration, performed by fitting a polygon with any number of sides to the object's outline, is driven by a new probabilistic model for the generation of polygons in a compact subset of R2, which is used as a prior distribution for the polygon. Some measurability issues raised by the correct specification of the model are addressed. The simulation from the prior and the calculation of the a posteriori mean of grey levels are carried out through reversible jump Markov chain Monte Carlo computation, whose implementation and convergence properties are also discussed. One example of restoration of a synthetic image is presented and compared with existing pixel‐based methods.
《日本民俗文化第11卷》（1986年）
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