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Perceptually Tuned Generation of Grayscale Fonts

Published: 01 November 1995 Publication History

Abstract

Previous attempts to generate grayscale fonts by filtering and resampling high-resolution masters produced fuzzy looking characters lacking sharp contrast profiles and uniform character structure elements (horizontal and vertical bars, curved stems, serifs). Contrast sharpness in vertical bars and repetitive contrast profiles of similar character structure elements must be preserved in order to avoid characters having fuzzy appearance. Furthermore, thin character parts must be enhanced so as to preserve their visual structure. A new grayscale character generation method is proposed which uses outline weight- and phase-control techniques for generating characters with bars and curved stems of predictable intensity profiles. The grayscale design knowledge of type designers has been made explicit and incorporated into the grayscale character synthesizing system. Knowledge about character structure elements is added to the character's outline description in the form of hints. Visual knowledge about the rendering of quality of the produced weight- and phase-controlled grayscale characters comes close to that of manually tuned grayscale designs. Accurate spacing of grayscale characters is obtained by using a model providing the area equivalent to the perceived intercharacter space. Such perceptually tuned and optically spaced grayscale characters may find applications in high-quality CRT and LCD displays.

References

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F. Crow, “The Use of Grayscale for Improved Raster Display of Vectors and Characters,” Computer Graphics (Proc. Siggraph), Vol. 12, No. 3, 1978, pp. 1-6.
[2]
J. Warnock, “The Display of Characters Using Gray Level Sample Arrays,” Computer Graphics (Proc. Siggraph), Vol. 14, No. 3, 1980, pp. 302-307.
[3]
J. Kajiya and M. Ullner, “Filtering High-Quality Text for Display on Raster Scan Devices,” Computer Graphics (Proc. Siggraph), Vol. 15, No. 3, 1981, pp. 7-15.
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A. Naiman and A. Fourier, “Rectangular Convolution for Fast Filtering of Characters,” Computer Graphics (Proc. Siggraph), Vol. 21, No. 4, 1987, pp. 233-242.
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G. Legge, et al., “Psychophysics of Reading — I Normal Vision,” Vision Research, Vol. 25, No. 2, pp. 239-252.
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M. Boschman and J. Roufs, “Comparison of Methods for the Evaluation of VDUs: The Effect of Bandwidth,” SID Digest of Tech. Papers, Vol. 21, pp. 17-20.
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W. Pratt, Digital Image Processing, John Wiley & Sons, New York, 1991.
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R. Hersch, “Font Rasterization: The State of the Art,” in Visual and Technical Aspects of Type, R. Hersch, ed., Cambridge University Press, Cambridge, 1993, pp. 78-109.
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R. Hersch and C. Bétrisey, “Model-based Matching and Hinting of Fonts,” Computer Graphics (Proc. Siggraph), Vol. 25, No. 4, 1991, pp. 71-80.
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Cited By

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  • (2020)SSNetNeurocomputing10.1016/j.neucom.2019.08.072371:C(15-26)Online publication date: 2-Jan-2020
  • (1997)Antialiasing of curves by discrete pre-filteringProceedings of the 24th annual conference on Computer graphics and interactive techniques10.1145/258734.258874(317-326)Online publication date: 3-Aug-1997

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Published In

cover image IEEE Computer Graphics and Applications
IEEE Computer Graphics and Applications  Volume 15, Issue 6
November 1995
106 pages

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 November 1995

Author Tags

  1. Digital typography
  2. grayscale characters
  3. grid-fitting
  4. optical spacing
  5. outline fonts
  6. typographic knowledge
  7. visual appearance.

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Cited By

View all
  • (2020)SSNetNeurocomputing10.1016/j.neucom.2019.08.072371:C(15-26)Online publication date: 2-Jan-2020
  • (1997)Antialiasing of curves by discrete pre-filteringProceedings of the 24th annual conference on Computer graphics and interactive techniques10.1145/258734.258874(317-326)Online publication date: 3-Aug-1997

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