Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (01): 62-66.doi: 10.13475/j.fzxb.20180300706

• Textile Engineering • Previous Articles     Next Articles

Image recognition algorithm based on yarn hairiness compensation and adaptive median filter

SUN Qiaoyan1(), CHEN Xiangguang2, LIU Meina1, SUN Yumei1, XIN Binjie1   

  1. 1. College of Engineering, Yantai Nanshan University, Yantai, Shandong 265713, China
    2. School of Chemical Engineering and Environment, Beijing Institute of Technology, Beijing 100081, China
  • Received:2018-03-01 Revised:2018-09-30 Online:2019-01-15 Published:2019-01-18

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Abstract:

In order to solve the influence of yarn hairiness on image recognition of yarn body in the process of yarn parameter recognition and calculation,an algorithm based on gray scale compensation and adaptive median filtering was proposed. R data were used to binarize the RGB image collected by the image scanner into a grayscale image. The image of the black yarn with white background was recognized according to the change of the vertical gray value in the feather form and then compensated by 3 layer push from small to large. The image of the white yarn with black background was recognized and the background gray value was compensated according to the gray value of the feather pixel. Each of the two compensated images were subjected adaptive median filtering (ANF) with a maximum window smaller than 11.The results of MatLab simulation show that the algorithm can recognize and compensate some pixels of yarn hairiness quickly and acquire clear main yarn image. The results can meet the requirements of accuracy.

Key words: hairiness compensation, adaptive median filter, recognition of gray threshold value, vertical direction recognition and push-wipe

CLC Number: 

  • TP319

Fig.1

Black background white transverse yarn original image"

Fig.2

Images processed by adaptive median filtering (a) and by inflation and corrosion operations (b)"

Fig.3

Image after black background transverse yarn compensation"

Fig.4

Images of black background longitudinal yarn compensation. (a)Original image; (b)Image after processing"

Fig.5

White background black yarn original image"

Fig.6

Flow chart of vertical direction recognition and pushing algorithm"

Fig.7

Result of processing images in Fig.5 with r=1 (a) and r=2 (b)"

Fig.8

Image processed by vertical direction recognition and massage compensation algorithm"

Fig.9

Final processed images."

Tab.1

Results comparison"

图片 理论直径/mm 测量直径/mm 误差率%
黑底横向白线 0.202 0.207 2.48
黑底纵向白线 0.202 0.205 1.49
白底黑线 0.205 0.203 1.00
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