The image threshold segmentation algorithm based on the Particle Swarm Optimization(PSO) combined with the rough entropy based on boundary region is presented.
提出一种基于微粒群优化(PSO)的边界区域粗糙熵的阈值图像分割算法。
参考来源 - 基于微粒群优化和粗糙熵的图像分割算法·2,447,543篇论文数据，部分数据来源于NoteExpress
提出一种基于微粒群优化(PSO)的边界区域粗糙熵的阈值图像分割算法。
The image threshold segmentation algorithm based on the Particle Swarm Optimization (PSO) combined with the rough entropy based on boundary region is presented.
粗糙集的不确定性度量方法，目前主要包括粗糙集的粗糙度、粗糙熵、模糊度和模糊熵。
Rougness, rough entropy, fuzziness, and fuzzy entropy are major methods for measuring the uncertainty of rough sets.
通过分析和实例可以看出，所提出的修正粗糙熵方法可以用来更合理、更精确地测量粗糙集中的不确定性。
The analysis and real example show that the modified rough entropy method for measuring uncertainty in rough sets is more reasonable and more accurate than the classical methods.
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