Assessment and Semantic Categorization of Fabric Visual Texture Preferences

Abstract

The texture of a fabric can be perceived by the haptic and visual senses. Visual texture can be defined as a visual quality of a surface. It is an important phenomenon because it can be significant in many fields, such as textile design and e-commerce. At the same time, when we consider the semantics of the word, it is important to take into account that there are a variety of manifestations of fabrics (e.g., woven, knitted, etc.). The mechanism of visual texture perception of fabrics was investigated by measuring visual evaluation values. In our experiment, 12 textile samples with different surface textures are evaluated using thirty-four adjectives (Kansei words). For each visual texture, the adjectives with the highest mean ratings are extracted and analyzed. By using Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), we aimed to discover and determine preferences for the visual texture of fabrics. The result is a semantic explanation of fabric texture with the adjectives proposed, which can help customers to evaluate the quality of the textile.

Keywords

• fabric
• hierarchical cluster analysis
• principal component analysis
• semantic meaning
• textile
• texture
• visual preference