Selecting an appropriate typeface is crucial in typography, web design, and other applications where text readability is essential. A key concept of this topic is legibility, the quality that shows how easy it is to recognize the letters of a particular font set. Previous works have measured legibility by human experiments, which has several limitations; for example, the methodology and circumstances were not entirely uniform, and the results may be distorted by the fatigue of the test subjects. This paper presents a new method using self-developed software to substitute human measurements in legibility testing. The software simulates the human retina's distortion effects (direction-dependent acuity) on test images of the assessed font's characters. Then, its output is analyzed using optical character recognition software. By integrating these techniques, we model the optical, biological, and cognitive steps of human character recognition as well. Although the simulation is imperfect, the software can perform significantly more measurements than human experiments with higher uniformity and give reproducible legibility information about significantly more fonts in various circumstances. In addition to the two scaling methods used in the literature (x-height, font-height), the tests are also performed with two other self-developed scaling methods, which provide a fairer comparison in the case of non-standard character types. This paper contains the legibility measurement results for 22 fonts under various simulated scenarios. The derived font ranking aligns closely with findings from prior human-based studies, demonstrating the robustness and reliability of the proposed method. Moreover, this approach provides valuable insights into font legibility across a broader spectrum of use cases, highlighting its potential for practical applications in typography and design.

Selecting a good typeface (or font) has a high importance in typography, web-design, ergonomics and similar fields. A key concept of this topic is the legibility of the fonts, which measures how easy it is to recognise the difference between the letters in a specific typeface. The typical investigations to measure this feature are based on human experiments. In this paper, a new approach and a simulation software are proposed to measure font legibility. A program, that simulates the distortion effects of the human retina is applied to test images of characters and optical character recognition software is used to investigate its output. This way the optical, biological, and cognitive steps of human character recognition is modelled. Although, the simulation cannot be perfect, the computer program can investigate much more fonts, characters with a lot of settings (e.g. for different visual acuity) than human experiments and gives reproducible results that are independent of fatigue, misunderstanding and other human limits.

Understanding mesopic vision is one of the hottest topics in lighting engineering [1]. The high importance of the field comes from the wide variety of the applications such as driving and other outdoor activities are performed in mesopic conditions at night. Therefore, it is extremely important to calculate the visibility of different objects in such conditions. In this paper, we present the algorithm and the first results of software, which is able to simulate the behaviour of human retina in scotopic, mesopic and photopic ranges, calculates the direction-dependent acuity. Our aim was to produce a practical tool to examine real-time situations. Therefore, classical camera recordings are used as input, which limits the accuracy but extends the range of applications.