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。

应用图像空域法的针织物密度在线测量

人工测量针织物密度的方法存在耗时、不能连续测量的缺点,且人工测量也无法满足在线控制针织物密度的要求,为此,提出一种应用空间域法对针织物图像处理得到其密度的方法。在针织物二值化图像基础上,根据针织物纹理特点提取出表征织物横密的纱线后,应用改进的Hough变换检测得到图像中针织物的横纱数目;然后根据横纱提取每行线圈,采用核密度估计对针织物线圈间距的统计量进行密度估计,得到标准的线圈间距,进而计算得到图像中横向平均线圈数;再通过换算得到针织物的密度。验证结果表明该方法实用有效。

基于纹理提取的针织物密度检测

为提高针织物密度检测准确度和检测效率,在针织物图像基础上,通过增强图像对比度并运用理想高通滤波实现织物高频增强提取针织物圈柱图像,运用形态学运算处理针织物圈柱图像,检测得到图像中圈柱数目。将圈柱图像细化处理获取圈柱骨架,针对骨架特点提取纵行纹理,进而检测针织物纵纱数量,得到横向线圈数,根据总的圈柱数目和纵纱数目得到纵向圈柱数,进而计算针织物线圈密度,实现针织物密度的自动检测。试验结果表明:该方法可以快速、准确地检测纬编针织物密度。

Measuring Structural Parameters of Knitted Fabrics by Digital Image Processing Techniques

In the knitting industry the measurements of the stitch density and the stitch length are usually done manually, which may lead to lower efficiency and less definition and also bring subjective ideas into the test results. In order to improve the effect we can measure with Digital Image Processing Techniques. A piece of sample is scanned into computer and changed into a digital image, which is processed with media filtering. To acquire the power spectrum, the image in the spatial domain is converted into the frequency domain. Picking up the characteristic points describing the stitch density and the stitch length separately in the power spectra and reconstructing them, the values of the stitch density and the stitch length could be calculated. When measuring the stitch length, we should establish a geometric model of the stitch based en the digital image processing, which provides a method to transform the stitch length in the two-dimensien space into the three-dimensien space and to measure the value of the stitch length more accurately. This method also provides a new way to measure the stitch length without damaging the fabric.