To construct a new publishing system using PC and large-sized printer that can produce high quality printed matters comprising text, charts, and illustrations, etc, a novel coding method is needed to ensure the quality of decoded images even on Affine-transformed enlargement or reduction. Conventional coding methods, however, cannot claim to have satisfied such a requirement. This paper proposes an algorithm for encoding and decoding binary images by adaptively approximating the contours using Fluency functions in the form of straight lines, arcs, and curved lines that were proposed by one of the authors. Also, in this paper, we derives compactly supported sampling function of degree 2 to approximate curved lines with accuracy and simplicity. In order to demonstrate the usefulness of our proposed coding method, we implemented a publishing system on a PC. Using this system, we compared our method and the MMR format in terms of the visual quality of decoded images and compression ratio based on the CCITT test documents. From the experimental results, we demonstrate that the quality of the decoded images was also maintained without the jaggy noises even on resizing. Furthermore signboards produced by our publishing system have actually been used in several live events.
