Abstract
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 more general analysis independent from letter shapes. 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, and (3) several impressions are very irrelevant to parts.
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Notes
- 1.
As noted in [23], it is also possible to use another operation than the summation, such as element-wise max operation.
- 2.
Fonts whose stroke is filled with textures such as “cross-hatching” give a huge number of SIFT descriptors because they have many corners. They inflate the average number of L; in fact, the median of L is 1, 223. In the later histogram-based analysis, we try to reduce the effect of such an extreme case by using the median-based aggregation instead of the average.
- 3.
Recall that the original SIFT vector is a unit vector, i.e., \(\Vert \mathbf {x}^i_l\Vert =1\).
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Acknowledgment
This work was supported by JSPS KAKENHI Grant Number JP17H06100.
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Ueda, M., Kimura, A., Uchida, S. (2021). Which Parts Determine the Impression of the Font?. In: Lladós, J., Lopresti, D., Uchida, S. (eds) Document Analysis and Recognition – ICDAR 2021. ICDAR 2021. Lecture Notes in Computer Science(), vol 12823. Springer, Cham. https://doi.org/10.1007/978-3-030-86334-0_47
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