Abstract
The specification of image content is a critical issue in image databases. In this paper we explore the problem of specifying an important visual cue, that of image texture. The approach we have taken is to separately categorize texture images and texture words (in the English language), and then explore the relationships between the identified categories of images and words. These relationships are expressed as association matrices, and measure the mapping between the visual texture space and lexical texture space. Based on experiments with human subjects, we determined Pearson's coefficient of contingency (which measures the degree of association) to be 0.63 for the association matrix mapping images to words, and 0.56 for the association matrix mapping words to images. These indicate a strong association between texture words and images. Furthermore, like categories of texture words map onto like categories of texture images, e.g. words dealing with repetition map onto images of repetitive texture.
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