Computer Text Shading Algorithm
||None; publication of the Human Factors and Ergonomics Societ|
Sehchang Hah, PhD.
Hah, S., & Hickey, T. (2001). Computer text shading algorithm based on perception of luminance. Proceedings of the 45th Human Factors and Ergonomics Society Annual Meeting, Minneapolis, MN. 622-226.
With raster display systems, images on a monitor show jaggedness, because they are defined by integer coordinates of the monitor. This jaggedness is called an aliasing effect. To reduce this, engineers developed algorithms. One well-known algorithm is supersampling. This is accomplished by sampling at a higher resolution and reducing the sampled data to a lower resolution. We overlaid arrays of a 3x3 matrix on a text (supersampling) and reduced each array to a pixel on a monitor. In this process, engineers determined the level of the pixel luminance-intensity linearly to the number of elements painted in each array. Instead of using such direct, linear transformation, we determined the level of brightness, not the level of the pixel intensity, to produce better shading. Brightness, not luminance, is subjective. We created nine sets of gray levels based on this algorithm. We ran two experiments to choose the optimal gray-level set. In Experiment 1, participants chose the more legible of two letters shaded with different gray-level sets. In Experiment 2, participants counted target-letters in a string of letters as fast as they could. The experimental results did not favor gray-level sets that were close to the traditional linear transformation from the number of painted elements in arrays to pixel luminance-intensity. The best set was actually the third brightest as identified with this procedure using human participants. This perceptual algorithm can be used for any monitor to reduce aliasing effect.
Updated: May 04, 2012 11:21 AM