5. The method of claim 1, additionally comprising identifying a plurality of additional clusters of pixels, each cluster representing a character.
1. A method of creating a decision tree to enable a character recognition device to recognize characters in a first font, comprising: scanning a document printed in said first font to generate an array of pixels, each having a neighborhood state; identifying a cluster of pixels in said array representing a character; selecting a pixel in said cluster; addressing a memory with the neighborhood state of said selected pixel, wherein said memory has stored in it a probability table providing the probability, in a second font different from said first font, that a pixel is black is a function of its neighborhood state, in which the neighborhood state of each pixel in the second font was determined in exactly the same way as the neighborhood states of the pixels in the first font; reading from said memory the probability of black associated with the neighborhood state of said selected pixel and assigning said probability to said selected pixel; and generating a decision tree for said first font using said assigned probability of black.