RavennaRandom-Xbold-Italic
Similar fonts
- ATS Bandipura Bold
- BigVesta ExtraBold Italic
- Blaster Demo
- CCExcaliburStone-Italic
- CCHighJinkies W00 Regular
- FagoNo-ExtraBoldCaps
- FagoNo-ExtraBoldtalicCaps
- FagoNoExb-Caps
- FagoNoExbLf-Caps
- FagoNoExbLf-ItalicCaps
- FagoNoExbTf-Caps
- FagoScTurk-Xbold
- FagoStd-ExBdCps
- FranklinGothicHandDemi
- FSP DEMO - RB93StlMdrnSP-39CS Bold Italic
- FSP DEMO - RB93StlMdrnSP-39DTP Bold Italic
- FSP DEMO - RB93StlMsBlntSP-39DTP Bold Italic
- HagridText-BoldItalic
- InfinitiMetaBlack-Caps
- Interact 03 18 Trial
- Interact 06 18 Trial
- LibeTypewriter Bold
- Meta Black Lf Caps
- MetaBlackCapsC
- Noobys Display
- Noobys Free Regular
- OPTIMoldy-DemiBold
- Queue Bold Regular
- Signa SC Offc Cond Black Italic
- Slabber Medium
- Texicali X Extra Bold Italic
- Udlap Display Sc Black
- Voxity SemiBold
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.