为了给出图像类推算法的适用范围，提出了一种新的基于分形维数向量的图像的相似性度度量算子。
To give applicable range of image analogies algorithm, based on the fractal dimension vector, a new operator used to measure the image similarity is proposed.
传统的K-均值算法选择的相似性度量通常是欧几里德距离的倒数，这种距离通常涉及所有的特征。
The Euclidean distance is usually chosen as the similarity measure in the conventional K-means clustering algorithm, which usually relates to all attributes.
本文给出了一种基于骨架树的线性骨架拓扑相似性度量算法。
After that a linear skeleton topological similarity measure algorithm based on skeleton tree is detailed.
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