Learning-based fuzzy colour prediction system for more effective apparel design

Chi Leung Hui, Tak Wah Lau, Sau Fun Ng, Chun Chung Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

Purpose - This paper aims to design and develop a learning-based fuzzy colour prediction system for providing more effective apparel design in computer-aided design system. Design/methodology/approach - In this study, we propose using a fuzzy system integrated with preliminary knowledge of colour prediction for facilitating apparel design. The performance of the proposed system is evaluated in terms of its computational efficiency and robustness. In addition, the proposed system is evaluated by target group of customers. Findings - It was found that the performance of the proposed system is better than the traditional approach. Research limitations/implications - Although the proposed system has some limitations, the outcome of this study could be used to produce a future breakthrough in providing an intelligent computer-aided design system for apparel product. Originality/value - Using such an approach, an apparel designer could predict the favourite colours of garment for a target group of customers. The system uses preliminary knowledge about the customers' profiles and evaluations. Such fuzzy approach for colour prediction is established, which is not used in a traditional way in apparel design.
Original languageEnglish
Pages (from-to)335-348
Number of pages14
JournalInternational Journal of Clothing Science and Technology
Volume17
Issue number5
DOIs
Publication statusPublished - 20 Oct 2005

Keywords

  • Clothing
  • Computer aided design
  • Control systems
  • Predictive process

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Materials Science (miscellaneous)
  • Business, Management and Accounting(all)
  • Polymers and Plastics

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