Finding similar fonts is a fundamental need for maintaining design consistency, preserving brand identity, and fostering creative flexibility. Fonts shape the visual language of a design, and the ability to identify similar fonts helps designers recreate specific styles, maintain visual harmony across multilingual content, and ensure accessibility. Existing tools like WhatTheFont, Fontjoy, and Adobe’s font recognition features in Photoshop, Illustrator, and InDesign have long provided font matching capabilities. However, these solutions primarily focus on the standalone properties of fonts.
In real-world designs, fonts are rarely used in isolation. They are applied to text content alongside typographic attributes such as line height, kerning, tracking, and drop caps. These attributes significantly influence how fonts are perceived within the context of a layout. As a result, fonts that appear similar in isolation may not visually align when combined with other design elements, posing challenges for designers aiming for cohesive results.
To address this limitation, we have developed an approach to design-aware font similarity. Unlike traditional methods, this approach considers not only the font itself but also its interaction with typographic attributes and layout context. By analyzing fonts in their real-world usage, this method identifies alternatives that visually match the overall design intent, ensuring harmony within the composition.
This enhanced capability transforms the design workflow by streamlining font selection, reducing iteration time, and empowering designers to deliver polished, cohesive results. Design-aware font similarity bridges the gap between font recognition and true design integration, setting a new standard in typography tools.
Rishav Agarwal
Sanyam Jain