Fit Instances wdth258
Similar fonts
- Fit Instances wdth245
- Fit Instances wdth246
- Fit Instances wdth247
- Fit Instances wdth248
- Fit Instances wdth249
- Fit Instances wdth250
- Fit Instances wdth251
- Fit Instances wdth252
- Fit Instances wdth253
- Fit Instances wdth254
- Fit Instances wdth255
- Fit Instances wdth256
- Fit Instances wdth257
- Fit Instances wdth258
- Fit Instances wdth259
- Fit Instances wdth260
- Fit Instances wdth261
- Fit Instances wdth262
- Fit Instances wdth263
- Fit Instances wdth264
- Fit Instances wdth265
- Fit Instances wdth266
- Fit Instances wdth267
- Fit Instances wdth268
- Fit Instances wdth269
- Fit Instances wdth270
- Fit Instances wdth271
- Inline TRIAL Normal Four
- Inline TRIAL Normal Six
- Inline TRIAL Normal Sixteen
- Inline TRIAL Normal Ten
- Scubik 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.