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The arguments regrading the importance of information theory with respect to this project vary. Information theory is indeed valuable due to its relevance to past projects in the field, on which future projects will rely. Image analysis is often involves the passage and handling of large sets of data and extraction of the meaning of the data is a necessity. Compression becomes ever more crucial when large models and entities are maintained in memory and, again, reasoning about compression goes back to the theory of information. New ways to encode data, avoid redundancy and describe objects succinctly are being sought as they often reduce the complexity of any system as well as its size. Measures of information are necessary to introduce and support learning capabilities which in turn form intelligent systems. Such systems can evaluate and judge improvement as illustrated thus far and as will be illustrated later.