Statistical analysis of human visual impressions on morphological image manipulation of gray scale textures

Abstract

A method of evaluating human visual impressions of gray scale textures using morphological manipulation is proposed. To study the effects of textural features on human Kansei, we introduced a texture analysis method based on mathematical morphology. Kansei is a Japanese word for sensibility or emotion. Kansei engineering is an approach to connect human sensibility with engineering applications. The proposed method allows us to manipulate global and local properties of a texture separately. Variations of textures were generated by repetitively modifying arranged objects and configurations of the arrangements of original textures. The manipulated textures were presented to human respondents and the similarity of those textures based on human impressions was evaluated. Hierarchical clustering was applied to the similarity matrix generated from respondents’ observations. The results of the human evaluation were compared with that of the objective similarity evaluation adopting six global textural features. The global features such as density, regularity, and directionality of the point configurations were shown to have significant effects on human visual impressions and identification of textures. In the case of a texture without significant characteristics in its point configuration, local features such as grain shape have an effect on visual impressions.