A body measurements and sensory evaluation-based classification of lower body shapes for developing customized pants design

• Published in: Industria textilă (Bucharest, Romania : 1994) Vol. 69; no. 2; pp. 111 - 117
• Main Authors: MIN, DONG, YAN, HONG, JUNJIE, ZHANG, KAIXUAN, LIU, MELISSA, WAGNER, HUIYU, JIANG
• Format: Journal Article
• Language: English
• Published: Bucharest The National Research & Development Institute for Textiles and Leather - INCDTP 01.05.2018
• Subjects: Abdomen; Arachnids; Body measurements; Classification; Clothing industry; Clustering; Customization; Design; Designers; Fashion designers; Fuzzy sets; Linguistics; Morphology; Set theory; Three dimensional bodies
• ISSN: 1222-5347
• DOI: 10.35530/IT.069.02.1381

In this paper, a fuzzy rough set-based classification method is applied to identify lower body shapes of a target population for developing customized pants design. First, a group of designers is selected for identifying the key dimensions and lower body shape indices related to women pants design. On the basis of this, we propose a classification algorithm, which uses triangle and trapezoid fuzzy membership functions for transforming the indices of the relevant data into five fuzzy sets, regarded as linguistic descriptors. An importance degree and a similarity degree are defined to solve conflicts of different indices. Next, we randomly select 125 human bodies in the target population and measure the key dimension values by means of a 3D body scanning system and then compute important body shape indices. Then, we set up a number of decision tables and respectively divide the shapes of various lower body positions into five classes by using the rough set method. The classification results have been validated by using a sensory evaluation procedure. The obtained results will effectively help to set up new garment sizes adapted to a target population and realize the concept of mass customization by developing personalized or customized garment styles.