Fit Instances wdth513
Similar fonts
- Fit Extra Wide
- Fit Instances wdth260
- Fit Instances wdth287
- Fit Instances wdth302
- Fit Instances wdth307
- Fit Instances wdth311
- Fit Instances wdth313
- Fit Instances wdth314
- Fit Instances wdth325
- Fit Instances wdth326
- Fit Instances wdth328
- Fit Instances wdth353
- Fit Instances wdth358
- Fit Instances wdth390
- Fit Instances wdth405
- Fit Instances wdth410
- Fit Instances wdth416
- Fit Instances wdth458
- Fit Instances wdth460
- Fit Instances wdth480
- Fit Instances wdth499
- Fit Instances wdth501
- Fit Instances wdth539
- Fit Instances wdth566
- Fit Instances wdth616
- Fit Instances wdth623
- Fit Instances wdth635
- Fit Instances wdth666
- Fit Instances wdth679
- Inline TRIAL Wide Four
- Inline TRIAL Wide Six
- Inline TRIAL Wide Ten
- Mischief 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.