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Applying Fuzzy clustering method to color image segmentation

机译:模糊聚类方法在彩色图像分割中的应用

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The goal of this paper was to apply fuzzy clustering algorithm known as Fuzzy C-Means to color image segmentation, which is an important problem in pattern recognition and computer vision. For computational experiments, serial and parallel versions were implemented. Both were tested using various parameters and random number generator seeds. Various distance measures were used: Euclidean, Manhattan metrics and two versions of Gower coefficient similarity measure. The F and Q segmentation evaluation measures and output images were used to assess the result of color segmentation. Serial and parallel run times were compared.
机译:本文的目的是将被称为模糊C均值的模糊聚类算法应用于彩色图像分割,这是模式识别和计算机视觉中的一个重要问题。对于计算实验,实现了串行和并行版本。两者均使用各种参数和随机数生成器种子进行了测试。使用了各种距离度量:欧几里得度量,曼哈顿度量和两个版本的高尔系数相似性度量。 F和Q分割评估措施和输出图像用于评估颜色分割的结果。比较了串行和并行运行时间。

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