用小波变换法自动测量机织物经纬密度

研究用小波变换方法对机织物图像处理,实现织物经纬密度的自动测量,提出了确定小波分解层次的方法,对分解图像进行二值化和平滑处理的方法,实验证明用coiflets小波处理织物图像是有效的。     

织物经纬密度自动测量的研究现状及其展望

介绍了目前国内外织物经纬密度自动测量的研究现状、研究方法以及推向市场的测量仪器的情况,并对织物自动测量的研究方法和技术进行了展望。     

织物经纬密度测量的研究进展

介绍了当前织物经纬密度测量的技术手段和国家标准，综述了当前国内外织物经纬密度自动测量的研究现状和进展以及投入应用的测量仪器的情况，并对新的测量仪器进行展望。     

基于频域特征点提取的素色机织物密度识别算法

通过计算机图像处理技术对织物图像进行分析,利用傅里叶变换技术将织物图像从空间域转换到频率域,并采用对比度拉伸、高斯低通滤波等图像预处理手段来增强图像质量,然后使用阈值处理技术对织物频谱图进行处理,得到包含织物密度信息的特征点坐标。通过频谱图上特征点坐标和空间域周期的对应关系,经计算最终得到织物经纬密度。实验结果表明,织物密度识别最高误差为2.8%,此方法可以实现三原组织素色织物的经纬密度的自动识别。     

用图像处理技术快速检测机织物的经纬密度

文章讨论了用一维傅立叶变换、二维傅立叶变换和小波变换等图像处理技术检测织物经纬密度的原理和方法,找到了一种快速、可靠的织物经纬密度的检测方法.用VC 编程实现了织物经纬密度的快速检测,并用三维立体图表示出织物图像的变换结果.     

喷水织机织物的经纬密度设计

从织物的原料类别与线型、丝线纤度、组织结构、织物用途等方面分析了经纬密度设计的注意点，介绍了喷水织机常用组织下不同纤度时的密度设计参考值，以及等紧度设计经纬密度的方法。     

基于图像处理的梭织物密度分析检测

针对梭织物密度检测中存在的问题,提出一种基于图像处理的梭织物密度智能分析系统。该系统通过取像装置采集样品高清实时图像,对图像进行自动标定、分割及矫正,计算并输出织物样品的经纬向根数测定结果。与人工测量相比,智能分析系统的检测结果相对偏差小于5%,表明该方法适用于梭织物密度的自动分析检测。     

麂皮绒织物的设计

从织物原料、织物组织、经纬密度及缩率、线型等方面分析了麂皮绒织物规格配置的要点,可供设计同类织物参考。     

基于小波变换的机织物经纬密度自动检测技术

探讨了小波变换在机织物图像处理方面的应用,通过使用多层小波分解与单层细节重构,实现了对机织物经纬密度的自动测量;提出了一种利用最大相关系数算法自动确定小波重构层数的新方法,可使结果更客观、准确。     

基于自适应小波变换的织物密度测量

应用自适应小波变换技术以实现机织物密度的自动测量。先运用Wiener2和直方图均衡技术对织物图像进行预处理,增强图像的纹理特征;接着选取自适应小波技术对织物图像进行分解;再对分解得到的子图像进行二值、平滑等后处理;最后通过分析后处理图像的经纬纱线信息得到织物密度。试验结果证明,运用该方法能够准确测量3种基本组织的织物密度,是一种行之有效的方法。另外,还简要介绍了自适应小波的构造技术。     

应用混色纱纹理信息的纬编针织物模拟

为研究数码混色纱纬编针织物的外观色彩及纹影的模拟方法,利用图像处理技术对采集的图像进行平滑去噪,得到剔除细节的模糊图像,在Lab 空间下运用彩色图像硬聚类算法对平滑后的图像进行聚类分割,得到混色纱主体图像,获取其左右的边界和中心线信息;然后在经典的Pierce 线圈模型的基础上,利用混色纱主体图像的廓线信息完成由纱线到线圈圈弧和圈柱的映射;最终根据不同组织的圈弧和圈柱的覆盖关系,得到基本纬编针织物组织。结果表明,提出的纱线映射线圈算法,通过织物组织结构及密度可模拟混色纱纬编织物的混色色彩及外观纹影。     

A relationship between dry-relaxed warp-knitted fabric structure and curling distance

This study provides us information about relationship between curling and knitted structure and density of two-guide bar warp-knitted fabrics. Five standard warp-knitted fabrics are produced with three densities (Tricot, Locknit, three-needle Satin, Reveres Locknit and three-needle Sharkskin). Certain cut lengths of sample fabrics in both wale and course direction are analyzed through image processing to define curling value. A mechanical model, a function of fabric structure and yarn parameters, is also suggested to predict the curling force. The results of experimental and theoretical results show a greater curling value for course-wise cut in comparison to that of wale-wise in all warp-knitted structures and densities. The lowest curling value is found for three-needle Sharkskin structure in both directions and all densities.     

An improved gray line profile method to inspect the warp–weft density of fabrics

Image processing has become a tremendous tool for various fields of applications as well as for textile manufacturing industry in recent years. Inspection of fabric density is one of the major issues for fabric manufacturers in textile industries. In this study, an image processing method comprising of linear and nonlinear techniques for automatic inspection of warp and weft yarn density of fabrics has been proposed. By avoiding common problems of linear filtering such as blurring and localization, anisotropic diffusion filtering has been applied as preprocessing operation to enhance the edge region/boundaries between adjacent yarns of the fabric images. We conjecture that given a skewed gray level image, the number of peaks in the gray line profile of the image is minimized if the image is rotated in such a way that the inter-spaces between yarns are aligned with the vertical axis. Gabor filter, an orientation-sensitive filter, is applied to the skewed image at that angle to boost the edges between inter-spaces. The number of warp and weft yarn density has been inspected by applying gray line profile method. Simulations have been done on a wide range of fabric image data set. The results have shown that nonlinear and steered filters made a contribution to the performance of the method. The number warp and weft yarn densities are determined with an accuracy rates above 90%.     

A computer vision-based system for automatic detection of misarranged warp yarns in yarn-dyed fabric. Part I: continuous segmentation of warp yarns

In textile and garment industries, misarranged warp yarns of yarn-dyed fabrics disorganize the layout of fabrics and lead to poor product quality. This series of studies aims to develop a computer vision-based system for automatic detection of misarranged color warp yarns in terms of high efficiency and good accuracy. Four main parts are included in this series of studies: warp yarn segmentation, fabric image stitching, warp regional segmentation, and yarn layout proofing. This paper proposes a continuous segmentation method of warp yarns to detect the misarranged color warp yarns for yarn-dyed fabrics automatically, which is the foundation of the developed computer vision-based system. The proposed framework consists of two main components: warp yarn segmentation and fabric image stitching. Firstly, the sequence images of a fabric stripe are captured using a designed offline image acquisition platform. Secondly, the warp yarns in the sequence images are segmented by a sub-image projection-based method successively. Thirdly, the sequence images are stitched by a yarn-template matching method based on their warp segmentation results. Finally, the continuous segmentation result of warp yarns is saved for the further processing of warp regional segmentation and color warp layout proofing. The proposed method has been evaluated on 720 fabric images of five fabric examples with plain and 2/2 twill, and experimental results show that the proposed method can realize the continuous segmentation of warp yarns in yarn-dyed fabrics with the yarn segmentation accuracy of 97.43% and image stitching accuracy of 99.53%.     

纯棉纱线合股数对织物性能的影响

为研究纯棉纱线合股数对织物力学性能和保形性的影响,采用线密度相同的单纱、双股线、3股线、4股线4种股线类型,以适当的经、纬密分别织制成平纹、斜纹、缎纹组织的织物。对织物的拉伸性能、撕裂强力、拉伸弹性、折皱回复性、悬垂性、弯曲性进行测试与分析。结果表明:3股线织物的断裂强力和撕裂强力较大,4股线织物的断裂伸长率较大,双股线织物的拉伸弹性回复率较大;平纹织物仅有双股线织物的折皱回复性优于单股线织物,斜纹和缎纹织物的折皱回复性随合股数的增加均变差;双股线平纹织物悬垂性相对较好,但均没有斜纹和缎纹织物的悬垂性好;单纱织物的弯曲性能比股线织物好。     

结合图像频域和空间域的纬编针织物密度检测方法

为解决当前基于图像处理测量纬编针织物密度准确度不高、稳定性较差等问题,提出一种结合频域和空间域来测定针织物密度的方法。首先通过离散小波变换重构针织物线圈图像获得线圈结构清晰的图像,再分别提取线圈灰度及二值图的灰度曲线。利用提出的基于概率密度统计的波谷坐标校验算法,结合线圈坐标校验算法获得实际线圈所在列坐标;再利用八邻域广度优先搜索算法求出纬编针织物横、纵方向的线圈个数,得到针织物横密和纵密。结果表明,密度检测方法与人工测量数据相比误差小于1.7%,该方法适用性好,运算量小,准确率高,可实现纬编针织物密度的自动化测量。     

Packing of micro-porous yarns. Part II: optimization of fabric characteristics

This paper is concerned with the study of the characteristics of plain woven fabric produced with micro-porous cotton yarns in weft. The micro-porous yarns with varying packing densities and level of pore volumes are produced by changing proportion of PVA fibre content in the blend, yarn twist multiplier (TM) and spindle speed at ring frame. The micro-pores within the structure of the yarn have been created by dissolving the PVA fibres using washing treatment in hot water. A three-variable factorial design technique proposed by Box and Behnken has been used to study the interaction effects of these variables on the characteristics of fabrics. The influence of these three variables on the mechanical, handle and comfort properties of fabrics are studied, the response-surface equations for all the properties have been derived and the design variables are optimized for various fabric properties. Improvements in bending resistance, abrasion resistance and compressional characteristics have been observed with incorporation of micro-pores within the yarn structure. These fabrics with micro-pores have improved thermal resistance and moisture vapour transmission compared to that of 100% cotton fabric.     

Evaluation of diamond bar patterns on fabric surface using an image analysis technique

The main aim of this work is to study of the effect of yarn periodic irregularities on the plain weave fabric appearance using an image analysis method. The pattern of fabric faults was simulated using a prepared computer program. In the experimental stage, two different types of yarn were prepared. The first yarn was produced with a certain wavelength and the second yarn was prepared with a strong periodic irregularity using an open-end spinning machine. The wavelength of the open-end yarn fault was measured by using an Uster 4 automatic evenness tester. For practical examination, the yarns were used as weft in a shuttle loom machine and two types of fabrics were produced. Using image processing, the number and size of the diamond bar patterns, and also the theoretical wavelength of the weft yarn, were calculated. The wavelengths calculated theoretically were compared with the actual wavelengths of the weft yarns. The results showed an acceptable accuracy of the method.     

Automatic inspection of yarn-dyed fabric density by mathematical statistics of sub-images

To inspect the yarn-dyed fabric density automatically, an effective image analysis method based on mathematical statistics of sub-images is proposed in this paper. This method consists of two main steps: rough measurement and precise measurement. The rough measurement is based on projection curve of the whole fabric image. The fabric image is converted into HSV model from RGB model firstly, and then the projection curve of value is gained directly. The number of yarns is obtained by counting the number of peaks in the curve roughly. The precise measurement is based on projection curves of the fabric sub-images. According to the roughly estimated yarn number, the whole fabric image is divided into a certain amount of sub-images and the projection method is applied to all the sub-images, respectively. The probability distribution map of peaks is obtained by processing the projection curves of all sub-images and the positions of the yarn center are located in the frequency curve generated from the map by mathematical statistics method. The number of peaks in the frequency curve is counted, and, therefore, the number of yarns is detected, and the density can be calculated precisely. The experimental results proved that the proposed method is effective for yarn-dyed fabrics and can satisfy the requirement for production practice.     

Acoustic performance of woven fabrics in relation to structural parameters and air permeability

This work deals with the study of the acoustic characteristics of woven fabrics in relation to fabric structural parameters and air permeability. In order to achieve the objectives of the research, sound absorption coefficient of woven fabric samples was determined via impedance tube method. Samples with various pick densities and yarn twist were used. The effect of fabric thickness was analyzed using three and six layered test samples. Results showed that, while for all samples the minimum values of sound absorption were observed at frequency bands of 250 and 2000?Hz, the maximum sound absorption occurred at the frequency of 1000?Hz. Results also indicated that fabrics woven at pick density of 30?thread/cm exhibited higher sound absorption than fabrics woven at other pick densities. It was found that, noise reduction coefficient of three and six layered samples, woven at low pick densities showed significant increases in comparison to those woven at high pick densities. It was also established that samples woven with lower weft yarn twist absorb sound wave more efficiently. It was concluded that fabric air permeability can be used as a criterion of sound absorption behavior of woven fabrics.