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Browse Prior Art Database

Context-Dependent Character Image Formation

IP.com Disclosure Number: IPCOM000038845D
Original Publication Date: 1987-Mar-01
Included in the Prior Art Database: 2005-Feb-01
Document File: 1 page(s) / 12K

Publishing Venue

IBM

Related People

Bantz, DF: AUTHOR [+2]

Abstract

Improved readability of low resolution character displays and printers is achieved by displaying or printing from a family of stored models from which the appearance of a word is derived. Character form and intercharacter spacing are defined by the models that consider various aspects such as adjacent characters, line leading and justification. The resulting patterns are functions of words, not of individual characters. A word model, any sequence of characters delimited by spaces, is subject to stress derived from the requirements of justification. Simple models that are a single image are invariant to justification and are transferred from storage in a single copy operation. Another model has linear springs between successive characters that permit certain character spacing to be either expanded or compressed.

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Context-Dependent Character Image Formation

Improved readability of low resolution character displays and printers is achieved by displaying or printing from a family of stored models from which the appearance of a word is derived. Character form and intercharacter spacing are defined by the models that consider various aspects such as adjacent characters, line leading and justification. The resulting patterns are functions of words, not of individual characters. A word model, any sequence of characters delimited by spaces, is subject to stress derived from the requirements of justification. Simple models that are a single image are invariant to justification and are transferred from storage in a single copy operation. Another model has linear springs between successive characters that permit certain character spacing to be either expanded or compressed. Word models will thus vary. They can be categorized as either "fixed image" or "parameterized-image" or "procedural" models. With the fixed-image model, unvarying images of words are stored and have the same appearance at each occurrence. Positional errors are accommodated between words. Storage volume is large and word images are stored in gray scale or "antialiased" form that permits perceptual spacing of characters within a word to a small fraction of a pel (picture element). The parameterized-image model uses an interpreter to synthesize the image from its parameters and a data base of character images that a...