The characterization of patina components by X-ray diffraction and evolved gas analysis

Twenty observers searched for three–digit numbers on displays ranging in density from 10 to 50 items coded in one through ten colors. Search times increased linearly with density and showed a curvi...

Color Code Size for Searching Displays of Different Density

There is a very long tradition in designing color palettes for various applications, going back to at least the Upanishad. Although color palettes have been influenced by the available colorants, starting with the advent of aniline dyes in the late 1850s there have been few physical limits on the choice of individual colors. This abundance of choices exacerbates the problem of limiting the number of colors in a palette, i.e., in keeping them into a manageable quantity. For example, it is not practical for a car company to offer each model in hundreds of colors. Instead, for each model year a small number of color palettes is offered, each containing the colors for the body, trim, interior, etc. Another example is the fashion industry, where in addition to solid colors there are also patterns, leading to a huge variety of combinations that would be impossible to stock. The traditional solution is that of “color forecasting.” Color consultants assess the sentiment or affective state of a target customer class and compare it with new colorants offered by the industry. They assemble a limited color palette, name the colors according to the sentiment, and publish their result. Textile manufacturers will produce fabrics in these colors and fashion designers will design clothes, accessories, and furniture based on these fabrics. Eventually, the media will communicate these forecasts to the consumers, who will be admired by their cohorts when they choose colors from the forecast palette, which by then is widely diffused.

http://www.hpl.hp.com/techreports/2011/HPL-2011-230.pdf

Harmonious colors: from alchemy to science

In this paper we introduce a preliminary proposal for linguistic description of images. The approach is based on i) a hierarchical fuzzy segmentation of the image, ii) a collection of linguistic features describing each region, and iii) fuzzy spatial relations and locations. The procedure is independent from the way these elements have been obtained, and provides a description with the characteristics of a summary, i.e., a brief and accurate description of the whole image. As another characteristic of summaries, the method can be guided in the description by the user's preferences and interest. Remarkably, we are able to provide a description containing sentences about disjoint regions appearing in different levels of detail.

Describing images via linguistic features and hierarchical segmentation

An iridescent virus of the bollworm Heliothis zea (Lepidoptera:Noctuidae)☆

http://academic.oup.com/jaoac/article-pdf/39/3/894/32697474/jaoac0894a.pdf

Osborn R A

Papers

The ISCC-NBS Method of Designating Colors and A Dictionary of Color Names