应用图像处理的纱线黑板毛羽量检测与评价

doi:10.13475/j.fzxb.20170705406

摘要/Abstract

摘要：

针对目测法检测纱线黑板毛羽效率低、主观性强等问题，提出一种新的基于图像处理的毛羽检测方法。纱线黑板经扫描仪采集图像，然后进行中值滤波、二值化、形态学运算、局部阈值等处理，得到黑板毛羽图像，统计出毛羽像素点个数，提出评价黑板毛羽量的指标——M指数。采用原料、线密度和纺纱方式各不相同的纱线进行实验，测得18种纱线的毛羽M指数，与乌斯特仪得到的毛羽H值建立回归模型，两种测试结果之间的相关系数为0.975。6种纱线的验证结果表明，本文提出的毛羽检测法和建立的毛羽M指数能较完整地提取和评价整块纱线黑板毛羽，算法精度高、评定结果可信度好。

关键词: 纱线黑板, 毛羽, 图像处理, 局部阈值

Abstract:

Aiming at the low efficiency and subjectivity of the visual observation of yarn hairiness of blackboard, a new hairiness detection method based on image processing was proposed. Image was acquired by the scanner. Then, the image was processed by median filtering, binaryzation, morphological operation and local threshold to obtain the blackboard hairiness images, and the number of hairy fiber pixels were counted. In addition, M Index was proposed to evaluate yarn hairiness on blackboard. The experiments were carried out by using different types of yarn material, yarn density and spinning system. The hairiness M Index of 18 kinds of yarns were measured. The regression model was established with the H value tested by a Uster tester, and the correlation coefficient between them is 0.975.The verification results of six kinds of yarn samples show that the hairiness detection method proposed in this paper can be used to extract the whole blackboard yarn hairiness relatively completely, and the M Index can assess the quality of blackboard yarn hairiness, with high algorithm accuracy and good reliability.

Key words: yarn blackboard, hairiness, image processing, local threshold

陆奕辰王蕾唐千惠潘如如高卫东. 应用图像处理的纱线黑板毛羽量检测与评价[J]. 纺织学报, 2018, 39(08): 144-149.

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