Research On Pattern Recognition Of Weft Knitted Fabric Structure Based On Image Processing

Nowadays, in the field of Textile industry, analysis and recognition of knitted fabric mainly depend on manual work or special equipment. Though this way is authoritative, it is not easy to manipulate, and hard to master. Moreover, it is time consuming and tedious. So it has become necessary to research on how to get and analyze knitted fabric structure with computer automatically.In this work, we provide three algorithms, the first of which is based on character statistics, the second of which is based on PCA algorithm and the third of which is based on energy statistics to get and analyze knitted fabric construction parameters and structure using Digital Image Processing and Pattern Recognition technology, and develop the flow and technical route of automatic analysis of knitted fabric parameters and structure recognition. Then we depict particularly the algorithm of getting knitted fabric construction parameters-vertical and horizontal densities and coil distance, according to the character that knitted fabric's structure is periodic on space. Finally, the results of calculating are compared to the results of manual measuring.In this work, We provided the flow of weft knitted fabric structure analysis and recognition. First, the image of the sample is inputted to computer by scanner. Then abstract the characters from the image through image processing. Finally, the unknown image can be recognized by these characteristics. The first algorithm is that abstract the shape characters from the image based on chain code and shape number, and then recognize the variety of the kintt in the unknown image by the shape characters. The two algorithm is that reduce the dimension of the image data and abstract the global character, based on PCA algorithm, and then then recognize the variety of the kintt in the unknown image based on the distance between the test sample and the training samples. The third algorithm is that abstract the energy characters of the horizontal, vertical and oblique directions based on the Mallat algorithm and Coifl wavelet transforms, and then recognize the variety of the kintt in the unknown image.The technical route and algorithms we provided above, have gained feasibility validation and achieve applicable results, have certain theoretical value and use for reference in the domain. Because the shape number has no changes when the fabric sample is translated and revolved, we choose the shape number as the characteristic to come over the error during the sampling. Because the PCA algorithm can reduce the calculation by reducing the dimensiong of the image data, we choose the algorithm to speed up the process of the recognization. We choose the energy characters, because it can be used in the images of different sizes and color without complex pre-processing. The pattern draft recognition method has some innovation in this field, especially analyzing the weft plain knitted fabric, rib knitted fabric and pearl knitted fabric.