A Pattern Measure

TL;DR

This paper introduces numerical measures to evaluate the aesthetic interest of simple patterns based on element variety and symmetry, aiming to quantify visual appeal and distinguish organized from disorganized designs.

Contribution

It proposes two composite measures, L and C, for assessing pattern complexity and randomness, providing a quantitative approach to analyze visual patterns.

Findings

Measures differentiate simple from complex patterns

L correlates with human perception of interest

C characterizes randomness in arrays

Abstract

In this paper we propose numerical measures for evaluating the aesthetic interest of simple patterns. The patterns consist of elements (symbols, pixels, etc.) in regular square arrays. The measures depend on two characteristics of the patterns: the number of different types of element, and the number of symmetries in their arrangement. We define two complementary composite measures L and C for the degree of pattern in a design, and compute them here for 2x2 and 6x6 arrays. The results distinguish simple from high-variation cases. We suspect that the measure L corresponds to the degree that human beings intuitively feel a design to be "interesting", so this model would aid in quantifying the visual connection of two- dimensional designs with viewers. The other composite measure C based on these numerical properties characterizes the extent of randomness of an array. Combining symbol variety with symmetry calculations allows us to employ hierarchical scaling to count the relative impact of different levels of scale. By identifying substructures we can distinguish between organized patterns and disorganized complexity. The measures described here are related to verbal descriptors derived from work by psychologists on responses to visual environments.