基于数字图像处理的纱线毛羽检测

为了更准确地检测出纱线毛羽长度及其根数，在结合视频显微镜和图像处理技术的基础上，提出一种新的毛羽检测方法。首先采用MOTIC SME-140视频显微镜采集纱线图像，然后经过灰度变换、图像分割、形态学开运算、图像细化处理，得到完整的纱线条干图像和细化后的毛羽图像，接着以纱线条干边缘为基准线，对毛羽分割点进行判断，最后得出不同长度的毛羽根数。图像法检测结果表明各纱线片段的毛羽根数值较为稳定，并且检测结果与目测图像计数的结果非常接近。因此，本文所提出的毛羽检测方法较现有的光电检测方法更为准确、可靠。

Primary of yarn hairiness based on digital image processing

In order to detect the length and root number of yarn hairiness more accurately, based on the combination with video microscope and image processing technology, a novel hairiness detection method was proposed. The yarn images that captured with a MOTIC SME-140 video microscope were processed with grayscale conversion, image segmentation, morphology opening and image thinning sequentially in order to generate both the images of yarn core and thinned hairiness. Then considering the yarn core edge as the measurement baseline to judge the hairiness cut-point, hairiness root numbers of different lengths were finally obtained. The detection result of hairiness root number in each piece shows a significant stability, and is close to the result of visual counting. Therefore, the proposed approach of hairiness detection in this study is more accurate and reliable than the traditional photoelectric method.