Neuron-ExtraLight
Similar fonts
- Arias-CondensedItalic
- BCMikserRSB-Regular
- BoxedRoundLight
- CC The Story So Far Outline
- ClanPro-NarrBook
- ClanPro-NarrowBook
- Daimito Condensed Light
- EastmanCondensedAltTrial Regular Offset Italic
- Estandar Rounded W00 XLight It
- Etnier Light Oblique
- FOTArias-CondensedItalic
- FSP DEMO - ddln xtr Lght Cndnsd Regular
- FSP DEMO - ExtLt Cond Obli Italic
- FSP DEMO - ExtLt ExtCond SeObli Italic
- GoodHeadlinePro-Light
- HamburgSerial-Xlight-Regular
- Heading Pro Double Light
- Helsinki-ThinItalic
- Humana Sans ITC Light
- Humana Sans ITC Light Italic
- Just Done Italic
- NeuronAngled-ExtraLightItalic
- NNMedien-Italic
- Oddlini-ExtLtExtraCond
- Pathway Extreme 36pt SemiCondensed ExtraLight Italic
- Pathway Extreme 72pt SemiCondensed Light
- Progressiva-Light
- Roclette Pro Light
- Routine Variable ExtLt Ita
- Routine Variable ExtraLight
- Santa Ana Light Italic
- Sharp Grotesk Thai Light 17
- Terfens Light
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.