Computer Technology for Textiles and Apparel by Jinlian Hu

By Jinlian Hu

Desktop expertise has remodeled textiles from their layout via to their manufacture and has contributed to major advances within the cloth undefined. computing device expertise for textiles and clothing offers an summary of those cutting edge advancements for a variety of purposes, masking issues together with constitution and illness research, modelling and simulation, and clothing design.

The ebook is split into 3 components. half one offers a assessment of alternative computer-based applied sciences appropriate for cloth fabrics, and contains chapters on laptop know-how for yarn and upholstery constitution research, disorder research and dimension. Chapters partially talk about modelling and simulation ideas of fibres, yarns, textiles and clothes, whereas half 3 concludes with a evaluate of computer-based applied sciences particular to clothing and clothing layout, with issues starting from 3D physique scanning to the instructing of computer-aided layout to model students.

With its special editor and overseas workforce of professional individuals, computing device expertise for textiles and clothing is a useful software for quite a lot of humans fascinated about the cloth undefined, from designers and brands to fibre scientists and caliber inspectors.

  • Provides an summary of leading edge advancements in laptop know-how for quite a lot of applications
  • Covers constitution and disorder research, modelling and simulation and clothing design
  • Themes variety from 3D physique scanning to the educating of computer-aided layout to type students

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The behavior of the human eye is simulated by an electronic camera and the brain is replicated by a computer. Many successful attempts have been made to develop different image analysis algorithms or different objective evaluation systems for this purpose. This chapter will introduce the background and reference review of digital-based technology for fabric structure analysis and will present up-to date methods for systematic weave pattern recognition. 2 Background and literature review The industrial identification of fabric weave construction is still dependent on the naked human eye and a teasing needle.

14 The Gaussian functions calculated by AOP algorithms. 15 Profile reconstructed by the Gaussian functions. coincides with the yarn density profile. , 2008, 2010). 6 Analysis of yarn blend The combination of fibres from different types of material can give the resultant yarn certain characteristics which are unobtainable from a single component, such as strength, colour or effect. Therefore, blending is a common practice in yarn spinning. Traditionally, the blending composition of blended yarns has been analyzed by using human visual inspection, but such a method is time-consuming and subject to operation errors.

Lien H C and Lee S (2002), ‘A method of feature selection for textile yarn grading using the effective distance between clusters’, Text Res J, 72, 870–878. Murrells C (2008), ‘Twist liveliness of spun yarns and the effects on knitted fabric spirality’, PhD thesis, Hong Kong Polytechnic University. Murrells C, Wong K K, Tao X and Xu B (2007), Yarn snarling testing apparatus and method, US Patent 7219556 B2. Nevel A, Avsar F and Rosales L (1996a), ‘Graphic yarn grader’, Textile Asia, 27, 81–83. Nevel A, Lawson J B, Gordon Jr K W and Bonneau D (1996b), System for electronically grading yarn, US Patent 5541734.

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