Cognitive Weave Pattern Prioritization in Fabric Design: An Application-Oriented Approach

Dejun Zheng, George Baciu, Jinlian Hu and Hao Xu
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Dejun Zheng: Hong Kong Polytechnic University, Hong Kong
George Baciu: Hong Kong Polytechnic University, Hong Kong
Jinlian Hu: Hong Kong Polytechnic University, Hong Kong
Hao Xu: Hong Kong Polytechnic University, Hong Kong

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2012, vol. 6, issue 1, 72-99

Abstract: Weave patterns are amongst the most popular design patterns in society’s daily lives with numerous applications. In the fabric design process, designer selects weave patterns based on the cognitive interpretation of the material structure in the fabric texture. In the selection activity of weave patterns, texture indexing and prioritization are curial tasks. These are associated with a cognitive process of interpretation and understanding of the texture elements in the woven structure of fabrics. In this regard, the authors use an interdisciplinary approach to help designer select weave texture patterns through structure and texture features and implement new algorithms that take into account essential features or rules in fabric pattern design. The features and algorithms are designed based on the object-attribute-relation (OAR) model and a cognitive informatics model. Three essential cognitive features of weave patterns are proposed, (1) the complexity of patterns in the fabric production process, (2) the structural appearance feature, and (3) cognitive tracking features for weave patterns. The authors’ experiments on a wide variety of weave patterns show that the proposed approach is capable of effectively prioritizing the cognitive features of weave patterns in fabric texture design process.

Date: 2012
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