ARB 93 Steel NsBlunt SEP-39 CAS Bold
Similar fonts
- ARB 93 Steel Narrowe SEP-39 CAS Bold
- ARB 93 Steel Narrowe SEP-39 DTP Bold
- ARB 93 Steel NsBlunt SEP-39 CAS Bold
- Beardvans Solid Regular
- Bradwall-Regular
- DNEG Script Super Regular
- Fearless Black
- Fearless Black Oblique
- Fruity Cereal
- FSP DEMO - RB93StlNrrwSP-39CS Bold
- FSP DEMO - RB93StlNrrwSP-39DTP Bold
- FSP DEMO - RB93StlNsBlntSP-39CS Bold
- FSP DEMO - RB93StlNsBlntSP-39DTP Bold
- Gulamba
- HS Sporaces
- Kane Bold
- Kane W00 Bold
- Marry Dance Regular
- Merry Santa
- Pinkquin
- Populaz
- SansPlomb Black Condensed
- SansPlomb Condensed Black
- SansPlomb Super
- SansPlomb Super Oblique
- SansPlomb_TRIAL Condensed Black
- SansPlomb_TRIAL Condensed Black Oblique
- SansPlomb_TRIAL Super
- SansPlomb_TRIAL Super Oblique
- SansPlomb2024 Black Oblique
- Street Urban Regular
- The laroca Regular
- The Laroca Regular
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.