FujiCondensedItalic
Similar fonts
- ABC ROM Compressed Book Italic
- ABC ROM Compressed Unlicensed Trial Book Italic
- Balboa UltraLight
- BenchNine Regular
- CFJohnDoe-Regular
- Corpa Gothic Pro Medium Italic
- DispatchComp Light
- DynaGroteskDXC-Italic
- DynaGroteskLXC-BoldItalic
- DynamoDxcItalicDXC
- Fellbaum Grotesk Thin Italic
- FoundersGroteskXCond-Reg
- FujiCondensedItalic
- Hype 0900 SemiBold It
- NaN Holo X-Condensed Regular
- NaN Holo X-Condensed TRIAL Regular
- NaN Metrify A TRIAL XCondensed Regular
- NaN Metrify A X-Condensed Regular
- NaNHoloXCondensed-Regular
- New Herman Regular
- Novel Sans Ar XCmp Regular
- Novel Sans Cy XCmp Regular
- Novel Sans He XCmp Regular
- Novel Sans Pro XCmp Regular
- Ranga Regular
- Tablet Gothic Compressed SemiBold Oblique
- TabletGothicCompressed-Oblique
- TabletGothicCompressed-SemiBoldOblique
- Test Founders Grotesk X-Cnd
- Test Founders Grotesk X-Cnd
- Test Founders Gtsk X-Cond Reg
- VTCFellbaumGroteskItalic-Light
- Walshes
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.