Intro Head H UC_FF H1
Similar fonts
- Akrobat-Thin
- Asenka Outline
- Blimone-ThinInktrap
- Eastman Cmp Alt Trial Thin Ita
- Eastman Compressed Alt Thin Italic
- Eastman Compressed Thin Italic
- Extenda XS Trial 10 Pica Backslant
- FSP DEMO - Herokid Thin Narrow Regular
- FSP DEMO - Kelpt Sans B1 Thin Regular
- FSP DEMO - lltrp xCndnsd Thn Italic
- Galeana Condensed Thin
- HeadingNow 491 Cond Thin Ita
- HeadingNow Trial 491 Cond Thin Ita
- HillenbergOutline
- Interstate-ThinCondensed
- InterstateCondensed-Thin
- InterstateT-ThinCond
- Intro Head H UC H1
- Ioskeley Mono Thin Condensed
- KelptA1-Thin
- KelptSansB1-Thin
- KorolevPro-ThinCondensed
- Movida Condensed UltraThin
- Movida Narrow UltraThin Italic
- NATURE green
- Parco Thin
- Polin Condensed Hairline Italic
- Renew 491 Cond Thin Ita
- Superscience-HairlineCond
- Trial Figura Thin Condensed
- Trial-Figura Thin Condensed
- TRY Grtsk Thin Zetta Regular
- Vermouth Outline
Details
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.