The study has been conducted to create evaluation vocabulary pools for different areas of color application by supplementing the color image evaluation vocabulary presented by earlier studies. For the purpose, it questions the adequacy and objectivity in different areas of color application of the evaluation vocabulary with regard to previously widely-used sensational measurements, and develops image analysis models visualizing the positioning of evaluation vocabulary for different areas of color application. The scope of this study is as follows: building exterior colors and makeup colors, whose characteristics are quite different from each other. And color evaluation vocabulary has been extracted and compared in different areas of color application, while color sense evaluation has been conducted to create an image analysis model through structural analysis of evaluation vocabulary and perform the analysis of color image tapping into it.
The results of the study are summarized as follows. First, the vocabulary finally selected for different areas of color application included 54 words for architectural exterior finish and 54 words for make-up colors, which were classified into vocabulary appearing commonly for all categories and independent vocabulary to compare color evaluation vocabulary collected for different areas of color application, thus verifying the differentiation of evaluation vocabulary characteristic of different areas. Second, to analyze the structure of evaluation vocabulary for different areas of color application, evaluation vocabulary was grouped through group analysis, while multi-dimensional scaling was employed to position evaluation vocabulary for different areas of color application and thereby creates a visual space model. With this, the similarity among evaluation vocabulary could be expressed in distance, and the differentiation of evaluation vocabulary structure was verified for different areas of color application. Third, the image analysis model was used to analyze the color characteristics by creating a color palette for the image group for different areas of color application, while color palettes were compared by category for the common image group. Since this is a color analysis tool that can not only make an objective expression of images targeted for different areas of color application but also provide a structural explanation of the differentiation by category of the common image vocabulary, it is considered valuable as an image analysis model.
The study is significant, because differentiation of evaluation vocabulary has been verified for characteristics of different areas through a comparison of color evaluation vocabulary collected for different areas of color application. And by positioning evaluation vocabulary for different areas of color application and thereby creating a visual space model, the similarity among evaluation vocabulary could be expressed in distance, while the differentiation of evaluation vocabulary structure was verified for different areas of color application.