Abstract
We present a method to generate glyphs which convey complex information in graphical form. A glyph has a linear geometry which is specified using geometric operations, each represented by characters nested in a string. This format allows several glyph strings to be concatenated, resulting in more complex geometries. We explore automatic generation of a large number of glyphs using a genetic algorithm. To measure the visual distinctness between two glyph geometries, we use the iterative closest point algorithm. We apply these methods to create two different types of representations for biological proteins, transforming the rich data describing their various characteristics into graphical form. The representations are automatically built from a finite set of glyphs, which have been created manually or using the genetic algorithm.
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Pintilie, G.D., Tuekam, B., Hogue, C.W.V. (2005). Generation of Glyphs for Conveying Complex Information, with Application to Protein Representations. In: Butz, A., Fisher, B., Krüger, A., Olivier, P. (eds) Smart Graphics. SG 2005. Lecture Notes in Computer Science, vol 3638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536482_8
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DOI: https://doi.org/10.1007/11536482_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28179-5
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