STTR Phase I: IntelliStitch AI: Intelligent Computerized Embroidery Design Automation for the Textile Industry

STTR 第一阶段：IntelliStitch AI：纺织行业智能电脑刺绣设计自动化

• 批准号: 0060306
• 负责人: David Goldman
• 金额: $ 10万
• 依托单位: Soft Sight, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-01-01 至 2002-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0060306&HistoricalAwards=false
• 关键词: STTR; Phase; IntelliStitch; AI; Intelligent

This Small Business Technology Transfer Research (STTR) Phase I project builds upon the technology and success of the company's software product, one of the industry's first embroidery design automation systems. It provides the textile industry with simplified mechanisms for converting scanned artwork into high quality embroidery design data. This data is then utilized by commercial sewing equipment to produce the embroidered artwork that has become quite common on all types of garments and woven goods. Unfortunately, embroidered artwork is often quite expensive to produce. In many cases, it may substantially exceed the costs of the actual garments being imprinted. These costs arise from a variety of factors including an embroidered design's size, layout, and complexity. Well-designed embroidered artwork permits efficient production with high yields (i.e. causing very few defective items to be produced). Automating this design creation process provides additional benefits by eliminating the time consuming manual process that must otherwise be undertaken by a human expert. With these factors as the primary motivation, this research will investigate advanced artificial intelligence and machine vision mechanisms, such as neural nets and structural indexes, to substantially improve capabilities and performance. The advantages of a robust automation system to the textile industry are quite substantial. Creating sophisticated embroidery designs is a tedious, time-consuming activity requiring the skills of a human expert (called a digitizer). Even after this process has been completed, any miscalculations by the digitizer could substantially impede production on machinery. A well-designed expert system could inevitably eliminate these costs and perhaps even provide a level of quality that is not achievable by its human counterparts. Additionally, this research may also have broad application within other fields such as document processing or other areas where image understanding and interpretation is important.

这个小型企业技术转移研究(STTR)第一阶段项目建立在该公司软件产品的技术和成功的基础上，该软件产品是行业首批刺绣设计自动化系统之一。它为纺织行业提供了将扫描的艺术品转换为高质量刺绣设计数据的简化机制。这些数据随后被商业缝制设备用来生产刺绣艺术品，这种艺术品在所有类型的服装和编织品上都变得非常常见。不幸的是，刺绣艺术品的制作往往相当昂贵。在许多情况下，它可能会大大超过实际印制服装的成本。这些成本是由各种因素引起的，包括刺绣设计的大小、布局和复杂性。设计良好的刺绣艺术品可以实现高效率、高产量的生产(即几乎不生产有缺陷的产品)。通过消除否则必须由人类专家执行的耗时的手动过程，自动化该设计创建过程提供了额外的好处。以这些因素为主要动机，本研究将研究先进的人工智能和机器视觉机制，如神经网络和结构指数，以大幅提高能力和性能。强大的自动化系统对纺织业的优势是相当大的。制作复杂的刺绣设计是一项乏味、耗时的活动，需要人类专家(称为数字化者)的技能。即使在这一过程完成后，数字化仪的任何错误计算都可能严重阻碍机器的生产。一个设计良好的专家系统可以不可避免地消除这些成本，甚至可能提供人类同行无法达到的质量水平。此外，本研究在其他领域也可能有广泛的应用，如文档处理或其他图像理解和解释非常重要的领域。