Various fonts give different impressions, such as legible, rough, and comic-text.This paper aims to analyze the correlation between the local shapes, or parts, and the impression of fonts. By focusing on local shapes instead of the whole letter shape, we can realize letter-shape independent and more general analysis. The analysis is performed by newly combining SIFT and DeepSets, to extract an arbitrary number of essential parts from a particular font and aggregate them to infer the font impressions by nonlinear regression. Our qualitative and quantitative analyses prove that (1)fonts with similar parts have similar impressions, (2)many impressions, such as legible and rough, largely depend on specific parts, (3)several impressions are very irrelevant to parts.

翻译：各种字体给人以不同的印象, 如可读、 粗略和漫画文本。 本文旨在分析本地形状或部件与字体的印象之间的相互关系。 通过关注本地形状而不是整个字母形状, 我们可以实现字母形状独立和更全面的分析。 分析由新合并的SIFT 和 DeepSet 进行, 以便从特定的字体中任意提取一些基本部件, 并把它们汇总起来, 通过非线性回归推断字体的形状。 我们的定性和定量分析证明:(1) 具有类似部分的硬体有相似的印象, (2) 多种印象, 如可读和粗糙, 基本上取决于特定部分, (3) 不同部分的印象非常不相干 。