  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).
