单一视角下自适应阈值法的纱线毛羽识别及其应用

doi:10.13475/j.fzxb.20180404607

纺织学报 ›› 2019, Vol. 40 ›› Issue (05): 150-156.doi: 10.13475/j.fzxb.20180404607

单一视角下自适应阈值法的纱线毛羽识别及其应用

王文帝, 辛斌杰(), 邓娜, 李佳平, 刘宁娟

上海工程技术大学服装学院, 上海 201620

收稿日期:2018-04-19 修回日期:2019-02-12 出版日期:2019-05-15 发布日期:2019-05-21
通讯作者: 辛斌杰
作者简介:王文帝(1993—),男,硕士生。主要研究方向为基于图像处理技术的纱线外观参数检测。
基金资助:
上海市自然科学基金项目(18ZR1416600)

Identification and application of yarn hairiness using adaptive threshold method under single vision

WANG Wendi, XIN Binjie(), DENG Na, LI Jiaping, LIU Ningjuan

Fashion College, Shanghai University of Engineering Science, Shanghai 201620, China

Received:2018-04-19 Revised:2019-02-12 Online:2019-05-15 Published:2019-05-21
Contact: XIN Binjie

摘要/Abstract

摘要：

为更准确测量纱线参数信息,针对图像背景处理和阈值分割算法对纱线图像处理后毛羽信息损失严重的问题,提出自适应灰度增强及线形区域阈值分割算法。并用自制图像采集系统获取6种不同类型的纱线样本,进行图像识别算法的准确性和有效性验证。结果表明:提出的2种算法可明显减少纱线图像信息损失,并且具有良好的鲁棒性,图像法检测的纱线毛羽长度和数量与目测法相近;实现了纱线主体与背景的灰度对比度增强,避免单一阈值导致的图像分割效果差的影响,提高纱线毛羽的识别精度和测量准确性,为后续研究纱线毛羽检测系统提供有效纱线图像分析算法。

关键词: 纱线毛羽, 自适应灰度增强, 区域阈值分割, 图像处理, 图像分析

Abstract:

In order to measure the yarn parameter information more accurately, the image grayscale enhancement algorithm and the linear region threshold segmentation algorithm were proposed to solve the serious loss of hairiness information after yarn image processing with the image background processing and the threshold segmentation algorithm. Using the self-built image acquisition system, six different types of yarn samples were acquired, and then the accuracy and validity of the image recognition algorithm was verified. Experimental results show that the proposed two algorithms can significantly reduce the loss of yarn image information and have good robustness. The length and number of yarn hairiness detected by the image processing method are similar to those of the visual inspection method. The grayscale contrast of the yarn and yarn image background is enhanced, and the effect of poor image segmentation due to a single threshold is avoided, thereby improving the recognition accuracy and measurement accuracy of the yarn hairiness. The research results provide an effective yarn image analysis algorithm for the subsequent development of a commercial yarn hairiness detection system.

Key words: yarn hairiness, adaptive grayscale enhancement, regional threshold segmentation, image processing, image analysis

中图分类号:

TP319

王文帝, 辛斌杰, 邓娜, 李佳平, 刘宁娟. 单一视角下自适应阈值法的纱线毛羽识别及其应用[J]. 纺织学报, 2019, 40(05): 150-156.

WANG Wendi, XIN Binjie, DENG Na, LI Jiaping, LIU Ningjuan. Identification and application of yarn hairiness using adaptive threshold method under single vision[J]. Journal of Textile Research, 2019, 40(05): 150-156.

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试样编号	纱线成分	成纱方式	梳纱工艺	纱线线密度/tex
1^#	棉	环锭纺	精梳	14
2^#	棉	环锭纺	精梳	18
3^#	棉	环锭纺	精梳	26
4^#	棉	环锭纺	普梳	26
5^#	棉	转杯纺	精梳	28
6^#	涤纶	环锭纺	精梳	28

编号	毛羽长度/ mm	毛羽根数		偏差/%
编号	毛羽长度/ mm	图像法	目测法	偏差/%
	1	107.4	86.7	23.88
	2	23.3	22.3	4.5
1^#	3	5.1	5.1	0
	4	1.2	1.2	0
	5	0.6	0.6	0
	6	0	0	0
	1	127.3	87.6	45.32
	2	13.6	13.2	3.03
2^#	3	1.3	1.3	0
	4	0	0	0
	5	0	0	0
	6	0	0	0
	1	75.5	67.3	12.18
	2	10.1	8.7	16.09
3^#	3	0.9	0.9	0
	4	0.2	0.2	0
	5	0.1	0.1	0
	6	0	0	0
	1	107.8	92.3	16.79
	2	20.1	18.8	6.91
4^#	3	2.8	2.8	0
	4	0.3	0.3	0
	5	0.1	0.1	0
	6	0	0	0
	1	117.3	86.7	35.29
	2	23.1	19.6	17.86
5^#	3	2.6	2.6	0
	4	0.2	0.2	0
	5	0	0	0
	6	0	0	0
	1	76.3	63.8	19.59
	2	12.8	11.3	13.27
6^#	3	5.2	5.1	1.96
	4	0.3	0.3	0
	5	0	0	0
	6	0	0	0

单一视角下自适应阈值法的纱线毛羽识别及其应用

Identification and application of yarn hairiness using adaptive threshold method under single vision

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