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In perception research, various models have been designed for the encoding of e.g. visual patterns, in order to predict the human interpretation of such patterns. Each of these encoding models provides a few coding rules to obtain codes of a pattern, each code expressing regularity and hierarchy in that pattern. Some of these models employ the minimum principle which states that the human interpretation of a pattern is reflected by the simplest code of that pattern. That is, the simplest code according to a given complexity metric. The authors propose a new complexity metric. The metric is based on a formal analysis of the concept of regularity. Some conclusions of the analysis are sketched. The new metric accounts for the amounts of irregularity and hierarchy as represented in a code of a pattern, such that these two amounts can be added to determine the complexity of a code.