Abstract: A method for compressing a typographic font and recovering the original font from the compressed font, first extracts the outline of each glyph in the font in turn, and analyzes the outline to find all the dominant points. The curvature and slope(s) at the dominant points are collected for clustering at the font level. The dominant points are matched algorithmically and the outline is dissected into strokes. A normalized stroke descriptor is computed for each stroke so that similarities between strokes that are related by translation, rotation, reflection and scaling can be made explicit. Thus a stroke is described by its normalized descriptor along with translation, rotation, reflection and scaling parameters. After each glyph outline has been so analyzed, the curvature and slopes at dominant points are clustered. Also, the normalized stroke descriptors are classified so as to put similar strokes into the same class. Each of these classes is assigned a unique identifier.

Abstract: A novel method and system for operation in combination with a laser printer for expanding its character and typeface selection capability. The sequence and operation for this method and system include dividing a list of characters to be printed into a plurality of character groupings or collections, storing these character groupings or collections in a plurality of different memories or memory sites, and providing an input command signal to these memories or memory sites which corresponds to a selected character desired to be printed. The different memories or memory sites are addressed starting first with the memory or memory site storing the largest character grouping or collection having the most frequently used characters therein and then addressing the different memories or memory sites in sequence to or toward the memory or memory site storing the smallest number of less-frequently used characters therein.