ESRI Cartography
Similar fonts
- 6x7oct Alternate Regular
- BobbyRoughSoft-CondensedOutline
- Burford Extrude B Solo
- Cheko
- DealersShadows
- ENFANTDUKULT-Light
- FinoSans-UltraThinItalic
- Frank Thin Oblique Rough
- HanedaLight-Regular
- kruengprung
- La Pica Shadow
- Magical Unicorn Neue Pro Color Horn Color Noire COLR
- Magical Unicorn Neue Pro Color Horn Color Noire SVG
- Magical Unicorn Neue Pro Color Sans Color COLR
- neue UXUI Icons ExtraLight
- Nostromo Outline Black Rough
- Nostromo Outline Bold Oblique Rough
- Nostromo Rough Light Oblique
- Nullomis Thin Oblique
- Nullomis Wide Thin Oblique
- oh livey extras
- Putney Shaded W00 Shaded
- Pyte Legacy Library TEST Gyrator
- RJ Best Before Unlicenced Trial 74
- RushtardBonus-Regular
- SchulschriftB-L4
- snapix
- SofiaRoughShadowOne
- Storyteller Sans Cd Regular
- Superpointrounded
- Walter-PatternDot
- Zing Rust Line Shadow2
- Zombie Brains Outline
How are we calculating this?
We analyze each font added to FontBase locally using the opentype.js library. We render the text off-canvas and measure key characteristics: stroke width; difference between bold and thin strokes; the relation of "x" letter height to capital letters; width of the letters compared to height; "i" size compared to "w" size. From these calculated numbers, we then build weight, proportion, xHeight and contrast. We also analyze the font's naming table to retrieve the basic info like font name, foundry and style names. No fonts are uploaded to our servers in the process.
How do we determine similar fonts?
Based on the characteristics we retrieve, on each font page, we select the fonts that have all the same parameter numbers. For example, if a font has 0.6 weight, we select fonts from our database that are in the range of 0.5-0.7 weight. We do this with all parameters combined, resulting in a similar font selection.