DETAILED DESCRIPTION The display of contrast-controlled grayscale characters produces the best results if each individual character is adequatly rendered and, if necessary, stored as a character pixmap image for further use, and if the spacing between two successive characters is adapted to their respective shape combination, or, more precisely, to the perceived visual space between them.
The contrast controlled rendering of individual grayscale characters (parent application Ser.
No.
08/043,180) and the visually evenly spacing of two successive characters (present application) should be used jointly in order to achieve the best overall display quality.
In the following description, the terms grayscale character and variable intensity character are interchangeable.
Both terms refer to a character pixmap image, where the pixmap is composed of pixels having a given number of intensity levels, for example 4, 8, 16, 32, 64, 128 or 256 levels.
Variable intensity characters can also be used to display color characters by using the variable intensity as an interpolation parameter for interpolating between a foreground colour and a background colour.
The disclosed method can be applied to computers and terminals which display variable intensity characters so as to produce high-quality grayscale or colour characters.
The method can also be applied to variable intensity dot printers which either print dots whose size depend on the intensity level of the pixels of the produced character pixmap image or which print dots whose density depends on the intensity level of the pixels of the produced character pixmap image.
The term grid-fitting means the process of adapting character outlines to the underlying grid, so as to obtain discrete bitmap or pixmap characters having uniformly looking character elements such as vertical bars, horizontal bars, stems and serifs (for more explanations, see R.
D Hersch, C.
Betrisey, "Model-based Matching and Hinting of Fonts", Proceedings SIGGRAPH'91, ACM Computer Graphics, Vol 25, No 4, pp 71-80)
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Image Analysis 
