Automatic Identification Of Jacquard Warp Knitted Fabric Pattern

Jacquard warp knitted fabric which has a unique fabric pattern is produced by warp knitting machine with the jacquard device. For its delicate and varied patterns, soft feel, it's to be loved by many consumers, and is widely used as interior decoration, high-end lingerie fabrics and lace accessories. However, the process for designing this fabric patterns needs tracing by designers which is time-consuming, it can not meet the product requirements of the growing market updates.The topic for this situation, from a practical point of view, first mastered the basics of texture image segmentation, analyzed the unique texture characteristics of Jacquard warp knitted fabric patterns, followed by trying a wide range of texture image segmentation algorithms in the Visual C++.NET programming platform, against the texture for three different types of fabric, finally put forward three methods for automatic recognition of jacquard warp-knitted fabric patterns.In a detailed description of the identification method, the paper introduced the Jacquard warp-knitted fabric image acquisition and pre-process, then describes how to use the three texture image segmentation algorithm knitted for automatic identification. The first method is the iterative threshold segmentation method, for Jacquard warp knitted fabric with detailed textures, the filtered image then was treated by threshold segmentation, edge smooth, can be changed to an accurate pattern image; the second is based on the texture energy analysis, contrary to the more rough textured jacquard warp-knitted fabric with two texture regions, after convolution of fabric image and the Laws texture template, combined with the iterative threshold segmentation method, we generate a clear recognition image. The third is based on the wavelet transform, for fabric with three or more texture regions, texture changes from rough to meticulous. Using Mallat pyramid different scale wavelet transform, extraction the average energy and variance of Jacquard warp-knitted fabric as texture features, combined with K means clustering to identify the fabric patterns.Then tested and evaluated these methods, recognition results show that the proposed three algorithms can accurately and quickly obtain the fabric texture patterns of the appropriate type. Finally, the proposed algorithm is applied to warp knitted fabric CAD system, proven to be effective in reducing the workload of designers, and to accelerate design speed of Jacquard warp knitted fabric drafted patterns, but not lost its validity.The proposed algorithm is also applicable to other similar texture image recognition processing, it has some promotional value. The final paper also shows some prospects of the development of texture image segmentation technology.