Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (02): 39-43.doi: 10.13475/j.fzxb.20190204905

• Fiber Materials • Previous Articles     Next Articles

Research and application of algorithm for measuring hemp fiber cross-sectional parameters based on boundary tracking

ZHANG Zhengye1, XIN Binjie2(), DENG Na1, CHEN Yang1, XING Wenyu1   

  1. 1. School of Electronic and Electrical Engineering, Shanghai University of Engineering Science,Shanghai 201620, China
    2. Fashion College, Shanghai University of Engineering Science, Shanghai 201620, China
  • Received:2019-02-27 Revised:2019-11-15 Online:2020-02-15 Published:2020-02-21
  • Contact: XIN Binjie E-mail:xinbj@sues.edu.cn

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Abstract:

It is difficult to simultaneously measure the parameters of multiple fibers in the cross-section image of fibers. To solve this problem, an algorithm based on boundary tracking for measuring the cross-section parameters of hemp fibers was proposed. After the edges of hemp fibers were extracted by an edge extraction algorithm, an appropriate edge detection image was obtained by modifying sensitivity threshold of the edge extraction algorithm. The hemp fibers were then identified and marked by a boundary tracking algorithm. All hemp fibers in the image were marked by cyclic marking and path point coordinates of boundary tracking were preserved. Finally, the algorithm was used to measure the perimeter, area and roundness of hemp fibers. The experimental results show that the method can simultaneously measure cross-sectional parameters of several hemp fibers. According to the data of the standard circle used for testing, the circumference deviation and area deviation of hemp fibers measured by this algorithm are about 3% and 4% respectively, and the data error is small.

Key words: hemp fiber, cross-section parameter, boundary tracking algorithm, edge extraction, fiber image processing

CLC Number: 

  • TS127

Fig.1

Original image of hemp fibers(×20)"

Fig.2

Comparisons of algorithms(×220). (a)Direct binarization;(b)Algorithm in this paper"

Fig.3

Edge detection graph of canny operator(×220). (a)Adaptive sensitivity;(b)Sensitivity is 0;(c)Sensitivity is 0.3; (d)Sensitivity is 0.5"

Fig.4

8 Neighborhood direction code"

Fig.5

Single fiber boundary tracking chart"

Fig.6

Preprocessing (a) and boundary tracking(b)image(×220)"

Fig.7

Comparison of multi-fibres treatment effects. (a)Common algorithms;(b)Algorithm in this paper"

Tab.1

Statistics data of test circles"

圆的
直径/
像素		 理论
周长/
像素		 理论
面积/
像素2		 实际
周长/
像素		 实际
面积/
像素2		 周长
偏差/
%		 面积
偏差/
%		 圆度
20 62.8 314.2 64.3 332.0 2.4 5.7 1.009
50 157.1 1 963.5 160.8 2 041.5 2.3 4.0 0.990
150 471.2 17 671.5 506.6 18 456.0 7.5 4.4 1.030

Fig.8

Cross-sectional parameters of hemp fibers"

Fig.9

Roundness statistics of hemp fibers"

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