By J Hu
Laptop know-how has remodeled textiles from their layout via to their manufacture. This e-book displays the numerous advances which have been made in desktop applied sciences, masking a variety of themes from modeling to digital textiles and clothing. half 1 offers a evaluate of other desktop established applied sciences compatible for cloth fabrics. Chapters contain laptop know-how for yarn constitution, cloth defects and garment constitution. half 2 discusses modeling and simulation rules of fibers and textiles. Examples of subject matters comprise the modeling of yarn and clothes. half three concludes with a assessment of computing device established applied sciences particular to clothing, topics diversity from 3D physique scanning to digital textiles.
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Extra resources for Computer Technology for Textiles and Apparel (Woodhead Publishing Series in Textiles)
Their method, based on dual-side scanning, reportedly has higher recognition accuracy and reliability than other common image analysis methods [21, 22]. 3 The digital system for weave pattern recognition This newly developed method is based on dual-side scanning technology and the active grid model (AGM) and was created to identify the weave pattern of woven fabrics. The dual-side imaging system, based on the panel scanner, is illustrated in Fig. 1. It is able to create images of both the top and bottom of the woven fabric.
The board covered with the wound yarn is then examined and a visual appraisal of appearance is made based on the fuzziness, irregularity and visible foreign matter. Traditionally, the inspection is carried out by direct observation in which a skilled specialist visually compares the wound table with photographic standards labelled in Grades A, B, C and D, and then judges the quality of the yarn sample according to the standard definition. Recently, attempts have been made to replace the conventional observation method with computer vision to resolve the limitation of human vision in yarn appearance grading.
At the same time, image processing, computer vision and pattern recognition have achieved their respective high levels of progress. Those developments in digital technology bring new data acquisition apparatus, new data analysis and recognition approaches, thus providing an alternative objective method for yarn feature analysis. A generic diagram of digitalized yarn feature analysis is shown in Fig. 1. In this chapter, we will present the state-of-the-art digital technologies for yarn structure and appearance analysis.
Computer Technology for Textiles and Apparel (Woodhead Publishing Series in Textiles) by J Hu