article·2005-10-01

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

Chi Leung Hui, Tak‐Wah Lau, Ng Sau-Fun, C. H. Chetwyn Chan

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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.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Color perception and design · melanin and skin pigmentation · Olfactory and Sensory Function Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References

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