The layout of colored yarns in yarn-dyed fabrics is a significant part of designing and production in the textile industry, which is still analyzed manually at present. Existing methods based on image processing have some limitations in accuracy and stability. Therefore, an automatic method is proposed to recognize the layout of colored yarns and some other basic fabric structure parameters: the fabric density and weave pattern. First, a large dataset with fabric structure parameters is constructed. The fabric images are captured by a wireless portable device. Then the yarns and floats are accurately located using a novel multi-task and multi-scale convolutional neural network. Finally, a density-based color clustering algorithm is proposed to recognize the layout of colored yarns. The results of extensive experiments show that the proposed method can automatically identify the basic structure parameters with high effectiveness and robustness.

中文翻译：

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色织织物中色纱排列的认识

色织织物中色纱的布局是纺织行业设计和生产的重要组成部分，目前仍需人工分析。现有的基于图像处理的方法在准确性和稳定性方面存在一定的局限性。因此，提出了一种自动方法来识别彩色纱线的布局和其他一些基本的织物结构参数：织物密度和组织图案。首先，构建具有织物结构参数的大型数据集。织物图像由无线便携式设备捕获。然后使用新颖的多任务和多尺度卷积神经网络准确定位纱线和浮标。最后，提出了一种基于密度的颜色聚类算法来识别彩色纱线的布局。