Automatic Detection of Structure Parameters of Yarn-dyed Fabric

In this study, an automatic recognition system based on image analysis is constructed to identify the density, the color effect, the layout of color yarns, and the woven pattern of yarn-dyed fabric. To inspect the density, first the skew angles of yarns are detected by Hough transform and then the texture and boundary information of yarns are enhanced by steering filter and graygrads image. The yarns and floats are located in the enhanced images with gray-projection method. To get the color effect, FCM algorithm is used to classify the floats with the color features extracted from each float and the number of yarn colors obtained with cluster validity analysis. The color effect is then extracted from the color pattern obtained from the float classification results. To detect the layout of color yarns, a novel method is proposed in this study. The woven pattern of the yarn-dyed fabric is recognized based on woven fabric pattern database. Experiments on actual yarn-dyed fabrics show that the recognition system proposed in this study is effective for detecting the structure parameters of yarn-dyed fabric.