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Comparing Data Compression in Web-based Animation Models using Kolmogorov Complexity

In the last few years, the internet use is growing and web pages are being populated by multimedia objects. At the same time, traffic over the internet is growing and, consequently, the importance of data compression. This paper presents formal definitions of “compression algorithm”, “better compression algorithm”, “best compression algorithm”, “animation”, “better animation” and a methodology based on Kolmogorov complexity for comparing computer animation models. The comparison is related to data compression. Kolmogorov complexity is defined as the length of the smallest effective description of a binary string and it is a suitable quantitative measure of the string information contents. The method is theoretical and more qualitative than empirical and quantitative. We show an example of application, comparing GIF-based animation model with AGA-based animation model. This paper focuses on bitmap-oriented animation and data compression without loss, although the method may be applied to the general case.