1. A method for variable data differential gloss font image comprising: selecting a font character; sub-sampling the selected font character into a sub-sample result; scaling the sub-sample result back up to a desired full size result; selecting a first halftone cell having a first anisotropic structure orientation; selecting a second halftone cell having a second anisotropic structure orientation; and in a digital front end, applying the first halftone cell to the desired full size result and applying the second halftone cell to a background field for the desired full size result to produce a variable data differential gloss font image.
1. A method for variable data differential gloss font image comprising: selecting a font character; sub-sampling the selected font character into a sub-sample result; scaling the sub-sample result back up to a desired full size result; selecting a first halftone cell having a first anisotropic structure orientation; selecting a second halftone cell having a second anisotropic structure orientation; and in a digital front end, applying the first halftone cell to the desired full size result and applying the second halftone cell to a background field for the desired full size result to produce a variable data differential gloss font image. 2. The method of claim 1 further comprising generating a complete gloss font set where the various enumerated steps of claim 1 are iterated for each desired derivative font character until each desired derivative font image is generated and assembled into a new complete gloss font set.