Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (07): 158-162.doi: 10.13475/j.fzxb.20180801305

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Hairiness detection based on maximum entropy and density clustering

LI Pengfei, YAN Kai, ZHANG Huanhuan(), JING Junfeng   

  1. College of Electronics and Information, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
  • Received:2018-08-02 Revised:2019-04-01 Online:2019-07-15 Published:2019-07-25
  • Contact: ZHANG Huanhuan E-mail:zhanghuanhuan0557@163.com

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Abstract:

In order to calculate the number of yarn hairiness and hairiness length more accurately,a method based on maximum entropy and density clustering was proposed to detect the yarn hairiness length and root number. The yarn image was preprocessed by bilateral filtering to filter out the noise in the image and enhance the yarn hairiness characteristics. Then the maximum entropy was adopted to segment the preprocessed yarn image and remove the yarn. The hairiness were extracted and refined. Finally, the density clustering algorithm(DBSCAN clustering) was applied to classify the number of hairiness. In addition, the root and length of hairiness according to the number of classified hairiness and the number of pixels in each class were calculated. Compared with the visual method and the datum line method, the experimental results demonstrate that the proposed method is very close to the visual method and more accurate than the datum line method. Furthermore, it is shown that the proposed method is accurate and effective.

Key words: yarn hairiness, hairiness detection, maximum entropy threshold, density clustering

CLC Number: 

  • TP391.4

Fig.1

Block diagram of hairiness detection method"

Fig.2

Affecting situation of hairy statistics. (a) Hairiness disconnection; (b) Adjacent hairiness"

Tab.1

DBSCAN clustering statistics number of hairs"

图序 领域参数 不同长度(mm)毛羽根数
E M 1 2 3 4 5 6 <1
图2
(a)		 0.0~3.0 4~6 3 0 0 0 0 0 4
3.1~6.0 4~6 2 1 0 0 0 0 3
6.1~8.0 4~6 2 1 0 0 0 0 4
3.1~6.0 1~3 2 0 0 0 0 0 5
3.1~6.0 7~9 2 1 0 0 0 0 2
图2
(b)		 0.0~3.0 4~6 1 0 0 1 0 0 3
3.1~6.0 4~6 0 0 0 0 1 0 3
6.1~8.0 4~6 1 0 0 1 0 0 3
3.1~6.0 1~3 1 0 0 1 0 0 3
3.1~6.0 7~9 1 0 0 1 0 0 2

Tab.2

Classification of hairiness length"

样本
序号		 不同长度(mm)毛羽根数
1 2 3 4 5 6
1# 123 35 15 12 3 1
2# 83 45 20 9 4 2
3# 158 60 30 10 5 1
4# 140 50 20 18 5 3
5# 143 28 19 11 7 4
6# 151 47 11 6 4 2
7# 131 40 25 10 5 2
平均值 132.7 43.6 20 10.9 4.7 2.1

Fig.3

Original image of yarn. (a) Sample 1; (b) Sample 2; (c) Sample 3"

Fig.4

Hairiness extracted by proposed algorithm. (a) Sample 1; (b) Sample 2; (c) Sample 3"

Fig.5

Baseline method (0.5 mm per grid). (a) Sample 1; (b) Sample 2; (c) Sample 3"

Tab.3

Comparison of algorithm and baseline method, visual method"

样本 本文算法
计算的毛羽
长度/mm		 基准线法 目测法
测量
长度/mm		 相对差/
%		 测量
长度/mm		 相对差/
%
1.824 1.0 82.4 1.8 1.33
样本1 1.512 1.0 51.2 1.5 0.80
1.080 0.5 116.0 1.1 1.82
0.600 0.5 20.0 0.7 14.29
1.920 1.5 28.0 2.0 4.00
样本2 1.848 1.5 23.2 1.9 2.74
1.200 1.0 20.0 1.2 0.00
1.152 0.5 130.4 1.2 4.00
3.336 2.0 66.8 3.4 1.88
样本3 2.544 2.0 27.2 2.6 2.15
2.088 1.0 108.8 2.1 0.57
1.056 0.5 111.2 1.0 5.60
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