Emotion-Based Classification and Indexing for Wallpaper and Textile

Yuan-Yuan Su, Hung-Min Sun
2017 Applied Sciences  
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
more » ... re 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. The challenges of using dynamic color combinations for the proposed mapping method of color-emotion include dynamically determining the number of colors in the image, identifying the main color of the background and the foreground more accurately and pairing these chosen main colors with destination color combinations. The method developed by Su and Chang [22] is used to select the initial representative color points in the color space. No more than three cycles of the Linde, Buzo, and Gray (LBG) algorithm [23] are used to obtain the final representative color points by clustering. This study then proposes two novel algorithms: Touch Four Sides (TFS) and Touch Up Sides (TUS). This enables accurate identification of the background color and the other main colors. After feature extraction or emotion selection, it can help people or non-professionals to accurately and easily meet expectations of emotion, which are based on feelings. Figure 3 shows the schematic diagram for this method. The remainder of this paper is organized as follows. Section 2 reviews previous studies in related areas. Section 3 describes the proposed architecture, the processing of the feature extraction and the dynamic color combinations for the color-emotion in detail, and, finally, performing the progressing of Emotion Based Classification and Indexing (EBCI). Section 4 demonstrates the experiment and the results. Section 5 proposes a conclusion and makes suggestions for future work.
doi:10.3390/app7070691 fatcat:xc3cffdkfjfevg3b73imucg53y