Automatic Identification of Ramie and Cotton Fibers Using Characteristics in Longitudinal View, Part I: Locating Capture of Fiber Images

Zhong

Textile Research Journal

2011

It is an important topic to characterize the cross-sectional shape of profiled fiber for quality control of textiles and performance design. In this paper, we propose a new measure of the shape factor, which can be used to characterize the cross-sections of profiled fibers. Different from the existing indices of the shape factor which are based on the ratio of the radii of circumscribed and inscribed circles, the proposed measure uses the shape information residing in the boundary of profiled fiber cross-sections. It is defined as the coefficient of variation of the area sequence in the cross-sectional plane at each angular interval. The capacity of this measure is validated by various examples, which also indicates that the defined measure can distinguish the discrepancy degree between fiber cross-section and the area equivalent circle. It is robust and applicable to any arbitrary shape with solid cross-section, no matter whether it is convex or concave.

“…If the same shapes are ranked with respect to , a different ranking 1,2,9,6,13,15,7,8,16,11,4,3,22,12,20,17,14,10,18,19,24,5,21,23 is obtained. Especially for multi-leaf shapes No.…”

Section: Experiments Illustrating CV R2 Behaviormentioning

confidence: 99%

A new shape factor measure for characterizing the cross-section of profiled fiber

Zhong

Textile Research Journal

2011

“…For an unknown fiber sample, F 1 and F 2 can be calculated using Equations (1), and plotted in the X-Y plane of the space (Z = 0). The point can then be projected on the probability surfaces along the Z-direction, and the corresponding probability of the lyocell and cotton is then displayed.…”

Section: Analysis Of Indirect Parametersmentioning

confidence: 99%

“…As lyocell and cotton have many complementary properties, such as bending elasticity, deliquescent effect and gliding property, they are often blended for use in dresses and formal wear for better comfort and drape. The quantitative analysis of lyocell and cotton blends is important for manufacturers, dealers, retailers, service providers or suppliers of blended textiles, and for independent testing labs.In our previous research, an automatic system for identifying ramie and cotton fibers was designed [1,2]. The system can automatically capture a series of microscopic fiber images in the longitudinal view to form a panoramic image of long-fiber segments, and then locate each valid frame to capture well-focused fiber images.…”

mentioning

confidence: 99%

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Automatic Identification of Lyocell and Cotton Fibers Using Cluster Analysis

Textile Research Journal

Yan

et al. 2010

Lyocell is a cellulosic fiber manufactured through a more environmentally friendly process. As lyocell and cotton have many complementary properties, such as bending elasticity, deliquescent effect and gliding property, they are often blended for use in dresses and formal wear for better comfort and drape. The quantitative analysis of lyocell and cotton blends is important for manufacturers, dealers, retailers, service providers or suppliers of blended textiles, and for independent testing labs.In our previous research, an automatic system for identifying ramie and cotton fibers was designed [1,2]. The system can automatically capture a series of microscopic fiber images in the longitudinal view to form a panoramic image of long-fiber segments, and then locate each valid frame to capture well-focused fiber images. Six characteristic parameters based on the Y-projection and X-projections of fiber stripes [1-4] were established for the fiber classification. These parameters, denoted as P i (i = 1~6), are listed in Table 1. The correlation analysis of the six parameters for ramie and cotton fibers revealed that they are linearly dependent [2]. 1 In this study, we will expand the function of this system for lyocell and cotton fiber identifications. Since the image capturing and feature extraction methods remain the same, we will focus on more effective pattern recognition Abstract This study applies cluster analysis to identifying two frequently blended fibers, lyocell and cotton, based on the six characteristic parameters extracted from the automatic fiber identification system presented in the previous publications. Two independent parameters are first derived from the six characteristic parameters by using factor analysis. Second, a probability density distribution map of the two indirect parameters is established through sample observations. Finally, the clusters of lyocell and cotton fibers in the probability density distribution map are segmented according to contour lines and distance. The experiment showed that the accuracy of lyocell and cotton fiber identification with the cluster analysis is above 95%. Table 1 Definitions of six fiber parameters.P 1 The average width of a fiber. P 2 The number of wave crests in the fluctuant fiber-width curve with values over 25% of the average fiber width in the range of one millimeter. P 3 The projective width of the X projection.P 4 The average of the subpoints on the Y projection.P 5 The number of the wave crests in the X projection.P 6 The depth of the deepest trough in the X projection.

Journal of Engineered Fibers and Fabrics

“…However, all of these techniques have some associated problems-first, the measured values are clear and distinct only at the fiber boundaries, secondly, the measured values are relatively accurate only when the fiber network has fewer layers, and finally the cost of measurement is relatively high [23]. Multi-layer image fusion technology can acquire the microscopic images of materials by using a microscope image testing system that includes automatic focusing [24]. This system can collect a series of images in different layers that cover the depth of the target along with automatic focusing, and then conduct fiber edge image processing and refining on the collected image information of the materials.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Distribution of Fiber Orientation on the Mechanical Properties of Silk Fibroin/Polycaprolactone Nanofiber Mats

Yin

Xiong

2017

In this study, Silk Fibroin (SF)/Polycaprolactone (PCL) composite nanofiber mats were fabricated using an electrostatic spinning technology employing different drum rotation speeds. The morphology and tensile performance of the resulting nanofiber mats were characterized using thermal field emission scanning electron microscopy, multi-layer image fusion technology, pore size distribution analysis and uniaxial and biaxial tensile tests. The analytical results showed that the drum rotation speed had little effect on the diameter of the nanofibers, but it did effect the physical orientation of the nanofibers. When the drum rotating speed was lower than 2.38 m s −1 , the nanofibers were randomly distributed, and there was no obvious mechanical anisotropy in the fiber mats. However, when the rotation speed was as high as 11.88 m s −1 , the nanofibers were fully uniaxially oriented, which provided high mechanical anisotropy to the fiber mats. The distribution of the size of the aperture of the nanofiber mats was related to the distribution in the fiber orientation. If the degree of orientation of the fibrous layer was high, the variation in the individual fibers was low and the pore diameter of fibrous mats was smaller as a result of the centralized fiber distribution. In the case of the SF/PCL composite nanofiber mats fabricated with different drum rotation speeds, the variation in the mechanical performance of the resulting mat in biaxial tension was consistent with its performance in uniaxial tension; however, it was found that the fracture mechanism of fiber mats varied in biaxial tension and uniaxial tension.