Emotion-based classification and indexing for wallpaper and textile

Abstract

This study, based on human emotions and visual impression, develops a novel framework of classification and indexing for wallpaper and textiles. This method allows users to obtain a number of similar images that can be corresponded to a specific emotion by indexing through a reference image or an emotional keyword. In addition, a predefined color-emotion model is applied to deal with the transference between emotions and colors in the paper. Besides color and emotion, the other significant feature for indexing is texture. Therefore, two features-the main colors (the representative colors) and the foreground complexity of a color image-are adopted in the method. The foreground complexity (a pattern complexity) is also called the texture of the pattern in an image. Another contribution of this study is the new algorithms of Touch Four Sides (TFS) and Touch Up Sides (TUS), which can aid in extracting an accurate background and foreground for color images. The potential applications of this study can support non-professionals in finding suitable color-combinations based on emotions for many applications with the transference between emotions and colors, and to imitate the professional operation of the color matching such as interior design, product design, advertising design, image retrieval and other relative applications.