Visual and tactile cues for perceiving circular knit fabric structures in on-body garment images

The purpose of this study is to identify visual cues for distinguishing circular knit structures in on-body garment images within online environments and to empirically analyze the perceptual relationships among knit structures. Two experiments were conducted. In Experiment 1, eight experts with more than 7 years of experience were presented with 48 woven and knit garment images in random order and asked to freely describe their rationale when identifying circular knits. Analysis of the collected descriptors revealed that knit perception was systematized into three dimensions: Form, Drape, and Feel, from which 23 adjective pairs were derived. In Experiment 2, 20 experts evaluated 36 garment images composed of 12 types of circular knit structures on a 7-point scale for the 23 adjective pairs. Analysis through multidimensional scaling (MDS), hierarchical cluster analysis (HCA), and correspondence analysis (CA) revealed that knit structures were classified into four perceptual categories—flat-dense, linear-structural, patterned-ornamental, soft-cozy—and two perceptual dimensions were derived: structure cue priority versus texture impression priority (MDS: 25%, CA: 48%) and softness versus distinctness (MDS: 17%, CA: 25%). This study systematically identified the visual perceptual structure of knit structures in on-body garment images in online environments and provides foundational data for textile recognition in online fashion environments, digital merchandising, and the development of AI-based textile recognition systems.