Full metadata record
DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorZheng, Dejun-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/6814-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleIntelligent texture-based pattern search, classification and interpolation for woven fabric designen_US
dcterms.abstractIn the cognitive process of design activity, fabric designers conceive the color and texture composition not individually, but as an ensemble of tones, shades and tints that are created in the texture patterns of yarn and fiber materials. Perceptual features of natural textures as well as fabric textures have been extensively studied in the existing literature. However, no thorough investigation of the cognitive texture features of woven patterns in fabric design has been conducted so far. The present research uses cognitive informatics models to study fabric texture features in the process of woven fabric design. It provides a comprehensive framework to facilitate selecting and designing the fabric textures in the design process. The research framework comprises cognitive fabric feature analysis and fabric texture operations in fabric pattern design, namely, fabric search, pattern classification, and woven texture interpolation with color theme-based texture synthesis. A novel object-attribute-relation (OAR) model is used to study fabric texture digitization and texture feature analysis. A relation between the high-level cognitive features and low-level perceptual features of fabric patterns in design activity is described. The cognitive features in fabric design are used to develop fabric texture operations. Examples of how cognitive features can be used to perform texture selecting and synthesizing tasks are given. There are three major contributions of this study to existing fabric texture analysis and research. (1) The study reduces the gap between the cognitive features of fabric textures in the design activity and the perceptual features of the textures in material operations. (2) New approaches for fabric pattern design are developed based on the cognitive color theme and interpolated woven patterns. (3) The research findings illustrate that fabric texture digitization methods and cognitive feature extraction in design activity are major factors in developing effective fabric texture operations.en_US
dcterms.extent210 p. : ill. (some col.) ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2012en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.educationalLevelPh.D.en_US
dcterms.LCSHTextile design -- Data processing.en_US
dcterms.LCSHTextile fabrics -- Design.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsopen accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/6814