Typography-MNIST (TMNIST): an MNIST-Style Image Dataset to Categorize Glyphs and Font-Styles
This provides a new benchmark dataset for researchers in typography and cognitive science, enabling studies on readability and font properties, but it is incremental as it extends the MNIST format to a new domain.
The authors introduced Typography-MNIST (TMNIST), a dataset of 565,292 MNIST-style grayscale images covering 1,812 glyphs across 1,355 fonts, to support research in cognitive typography and font design.
We present Typography-MNIST (TMNIST), a dataset comprising of 565,292 MNIST-style grayscale images representing 1,812 unique glyphs in varied styles of 1,355 Google-fonts. The glyph-list contains common characters from over 150 of the modern and historical language scripts with symbol sets, and each font-style represents varying subsets of the total unique glyphs. The dataset has been developed as part of the CognitiveType project which aims to develop eye-tracking tools for real-time mapping of type to cognition and to create computational tools that allow for the easy design of typefaces with cognitive properties such as readability. The dataset and scripts to generate MNIST-style images for glyphs in different font styles are freely available at https://github.com/aiskunks/CognitiveType.