Ambigrams are graphical letter designs that can be read not only from the original direction but also from a rotated direction (especially with 180 degrees). Designing ambigrams is difficult even for human experts because keeping their dual readability from both directions is often difficult. This paper proposes an ambigram generation model. As its generation module, we use a diffusion model, which has recently been used to generate high-quality photographic images. By specifying a pair of letter classes, such as 'A' and 'B', the proposed model generates various ambigram images which can be read as 'A' from the original direction and 'B' from a direction rotated 180 degrees. Quantitative and qualitative analyses of experimental results show that the proposed model can generate high-quality and diverse ambigrams. In addition, we define ambigramability, an objective measure of how easy it is to generate ambigrams for each letter pair. For example, the pair of 'A' and 'V' shows a high ambigramability (that is, it is easy to generate their ambigrams), and the pair of 'D' and 'K' shows a lower ambigramability. The ambigramability gives various hints of the ambigram generation not only for computers but also for human experts. The code can be found at (https://github.com/univ-esuty/ambifusion).

翻译：对称字是一种图形化字母设计，既能以原始方向阅读，也能通过旋转（尤其是180度旋转）阅读。即使对人类专家而言，设计对称字仍具挑战性，因为保持双向可读性往往十分困难。本文提出了一种对称字生成模型，采用近年来用于生成高质量摄影图像的扩散模型作为生成模块。通过指定字母类别对（如'A'和'B'），该模型能生成多样化的对称字图像——原始方向可读为'A'，而旋转180度后则可读为'B'。实验结果的定量与定性分析表明，该模型能生成高质量且多样化的对称字。此外，我们定义了"双向可读性指标"，即衡量每对字母生成对称字难易程度的客观标准。例如，'A'与'V'组合表现出高双向可读性（易于生成对称字），而'D'与'K'组合则呈现较低双向可读性。该指标不仅为计算机，也为人类专家提供了关于对称字生成的多方面启示。相关代码已开源（https://github.com/univ-esuty/ambifusion）。