Matching and Retrieval Based on the Vocabulary and Grammar of Color Patterns

We propose a perceptually-based system for pattern retrieval and matching. There is a need for such an "intelligent" retrieval system in applications such as digital museums and libraries, design, architecture and digital stock photography. The central idea of the work is that similarity judgement has to be modeled along perceptual dimensions. Hence, we detect basic visual categories that people use in judgement of similarity, and design a computational model which accepts patterns as input, and depending on the query, produces a set of choices that follow human behavior in pattern matching. There are two major research aspects to our work: The first one addresses the issue of how humans perceive and measure similarity within the domain of color patterns. To understand and describe this mechanism we performed a subjective experiment. The experiment yielded five perceptual criteria used in comparison between color patterns (vocabulary), as well as a set of rules governing the use of these criteria in similarity judgement (grammar). The second research aspect is the actual implementation of the perceptual criteria and rules in the image retrieval system.