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Fibers and Polymers

, Volume 19, Issue 12, pp 2642–2656 | Cite as

Female Body Shape Classifications and Their Significant Impact on Fabric Utilization

  • T. Naveed
  • Y. ZhongEmail author
  • A. Hussain
  • A. A. Babar
  • A. Naeem
  • A. Iqbal
  • S. Saleemi
Article
  • 19 Downloads

Abstract

In apparel manufacturing, more than 50 % cost is consumed by the textile fabric. Therefore companies have significant apprehensions in the fabric utilization. It can result in more efficient and cost-effective in fabric utilization if they are related to different body shapes. The purpose of this study is to classify female body shapes and evaluate fabric utilization efficiency for each category of the body shape. To this end, three dimensional (3D) body scans are collected from 124 young female subjects. For the body shape analysis, 3D body scans are processed by using Moore neighbor algorithm and region prop function to perceive the outermost shell. Moreover, both front and side view of the scans is processed for data reduction using Principle Component Analysis (PCA) and clustering using K-Means ++. It has been observed through our analysis of a dataset that female bodies can be categorized into four body shapes, that is, oval shape, circle shape, triangle shape, and rectangle shape. It has also been observed that all four body shape categories exhibit dissimilar anthropometric size measures. The result implies that these body shapes have devoured different fabric utilization for the garments (fitted trouser and fitted shirt). It has been noted that in fitted trouser and fitted shirt the most effective is the rectangle shape (cluster 4) and the least is the circle shape (cluster 2) in the fabric consumption. Similarly, the fitted trousers utilize less fabric while the fitted shirts consume more fabric in all body shapes. These findings provide a better reference of fabric utilization and cost-effectiveness to the apparel manufacturers while producing garments for different categories of the body shape.

Keywords

Body shape clustering Moore neighbor algorithm Region prop function PCA Fabric utilization 

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Copyright information

© The Korean Fiber Society, The Korea Science and Technology Center 2018

Authors and Affiliations

  • T. Naveed
    • 1
    • 2
  • Y. Zhong
    • 1
    • 3
    Email author
  • A. Hussain
    • 1
  • A. A. Babar
    • 4
  • A. Naeem
    • 5
  • A. Iqbal
    • 6
  • S. Saleemi
    • 1
    • 7
  1. 1.College of TextilesDonghua UniversityShanghaiChina
  2. 2.School of Fine Arts, Design and ArchitectureGIFT UniversityGujranwalaPakistan
  3. 3.Key Lab of Textile Science and TechnologyMinistry of EducationShanghaiChina
  4. 4.State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and EngineeringDonghua UniversityShanghaiChina
  5. 5.Key Laboratory of Eco-textilesJiangnan UniversityWuxiChina
  6. 6.College of Computer ScienceDonghua UniversityShanghaiChina
  7. 7.Department of Textile Engineering and TechnologyUniversity of the PunjabLahorePakistan

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