Abstract
Men and animals instantly detect “regularity” and “constancy” in visual patterns (and, in general, their structural aspects) with high efficiency. Our approach to evaluating the structural content of a pattern starts from the definition of algorithmic information or complexity, given by Kolmogorov and Chaitin, in which we distinguish two parts containing the metric and structural aspects of the pattern. SIT theory, developed by Leeuwenberg et al. in the area of visual perception, allows one to evaluate efficiently the structural complexity of a linguistic pattern code. We analyse the formal properties of SIT in the context of the theory of reduction calculi.
This work was partially supported by ESPRIT Grant No.P940
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© 1988 Plenum Press, New York
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Martinoli, O., Masulli, F., Riani, M. (1988). Algorithmic Information of Images. In: Cantoni, V., Di Gesù, V., Levialdi, S. (eds) Image Analysis and Processing II. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1007-5_31
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DOI: https://doi.org/10.1007/978-1-4613-1007-5_31
Publisher Name: Springer, Boston, MA
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