Global study on data compression techniques for digital Chinese character patterns

Dot matrix representation of Chinese characters is the most popular method used, however, it requires a relatively large memory for the storage of Chinese character patterns. For the purpose of a global study, various data compression techniques are investigated to determine the method that requires the least amount of memory for data storage. The entropy of Chinese character patterns preprocessed using the two-dimensional prediction algorithm shows the best results and appears almost independent of the subblock resolutions of m*n. Therefore, a possible bound of data compression for Chinese character patterns can be predicted. The data compression technique involving two-dimensional prediction preprocessing as well as arithmetic coding for subblock symbols is found to be capable of achieving the best compression results for the 13051 Chinese character patterns with various fonts in different resolutions.