Pixel Classification Based on Gray Level and Local 'Busyness'

摘要

An image can be segmented by classifying its pixels using local properties as features. Two intuitively useful properties are the gray level of the pixel and the busyness, or gray level fluctuation, measured in its neighborhood. Busyness values tend to be highly variable in busy regions; but great improvements in classification accuracy can be obtained by smoothing these values prior to classifying. An alternative possibility is to classify probabilistically and use relaxation to adjust the probabilities. (Author)