Structural characterization and measurement of nonwoven fabrics based on multi-focus image fusion

Yang, Chen; Deng, Na; Xin, Binjie; Xing, Wenyu; Zhang, Zheng-Ye

doi:10.1016/j.measurement.2019.04.034

Cited by 16 publications

(6 citation statements)

References 15 publications

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“…With the spatial domain method it is difficult to obtain clear fiber edge information. The algorithm based on the NSST proposed by Chen et al 3 and the fusion algorithm based on multi-wavelet fusion and inverse transform proposed by Chen et al 4 only operated in the spectral domain on the image. These methods were not sensitive enough to provide the details of the image target.…”

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confidence: 99%

“…3 and the fusion algorithm based on multi-wavelet fusion and inverse transform proposed by Chen et al. 4 only operated in the spectral domain on the image. These methods were not sensitive enough to provide the details of the image target.…”

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confidence: 99%

“…In this study, the rule of a large absolute value was used to fuse the high-frequency sub-band, while the rule of large regional variance was used to fuse the low-frequency sub-band. Chen et al 4 proposed a novel multi-focus algorithm to characterize the structure of nonwoven fabrics. The image fusion algorithm was designed using multi-wavelets and the inverse transformation, where the image's high-and low-frequency components were filtered and combined using different fusion rules.…”

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confidence: 99%

“…3 For nonwoven fabric, microfibers could be considered the smallest units. 4 Therefore, image processing technology based on an optical microscope is among the most commonly utilized approaches for measuring morphological parameters, such as the fiber fineness, fiber orientation distribution and fiber arrangement structure, of nonwoven fabric. 5 Getting a clear image that contains all relevant objects in one area is the prerequisite for achieving high-precision optical measurements.…”

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confidence: 99%

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Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

Zhu

Sun

et al. 2023

Textile Research Journal

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In the microscopic imaging scenario where the object thickness exceeds the depth of field of the microscope, multi-focus image fusion (MFF) is an effective method to generate an all-in-focus image. However, for nonwoven fabric for which the captured image number is up to 100 or more, the existing methods often underperform in areas near the fiber edges, owing to image ghosting and noise accumulation caused by the platform moving. To address the above problem, this paper presents a method designed to fuse multi-layer micro-images based on the combination of spectral and spatial features of the images. Firstly, the spectral domain-based map is generated by decomposition and reconstruction of the high-frequency and low-frequency components of the images, aimed at obtaining the edge information. Simultaneously, the spatial domain-based fuse map is built through sharpness measurement, referring to visual perception. Finally, the two methods are combined via an optimized weight to obtain an all-in-focus fused image. Four groups of real-world data consisting of 100 multi-focus nonwoven images are utilized to verify the superiority of this method. The experimental results demonstrate that the proposed method can obtain satisfactory performance in terms of both human visual evaluation and objective evaluation compared with the image fusion framework based on the convolutional neural network, MFF, region-based image fusion algorithm and convolutional neural network state-of-the-art fusion methods.

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confidence: 99%

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confidence: 99%

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confidence: 99%

mentioning

confidence: 99%

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Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

Zhu

Sun

et al. 2023

Textile Research Journal

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“…For instance, fused images obtained with digital optical microscopy were used to measure the fiber diameter, porosity and orientation distribution function of nonwovens. 5 A new software based on image-processing techniques was employed to generate a computerized average fiber diameter from SEM images, and that technique was flexible even for varying fiber diameters and low-contrast images. 6 A computer-based image-processing tool was developed for a semiquantitative determination procedure for dye analysis using woven and nonwoven fabrics.…”

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confidence: 99%

Algorithm to determine local basis weight of random fibrous networks with X-ray microtomography and SEM images

Hewavidana,

Balci,

Gleadall

et al. 2023

Textile Research Journal

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Analysis of the basis weight for random fibrous networks is important to understand their microstructure, properties and performance. Two-dimensional microscopical images show in-plane fibers without giving any information on their distribution in three dimensions. This research introduces a fully parametric algorithm for computing the local basis weight of random fibrous networks using three-dimensional images because out-of-plane fiber orientation is important, especially for high-density or thick networks. Voxel models of real nonwoven webs were generated by an X-ray micro-computed tomography system. The developed algorithm could accurately estimate a local basis weight value for random fibrous networks produced with various manufacturing parameters. Numerical results computed with the developed method were compared with those obtained with a physical weight measurement technique. The algorithm was tested and validated for various nonwoven fabrics with different densities. It was observed that the developed method can be used to examine and/or compare the basis weight of a wide range of random fibrous networks. In addition, it can be used to predict the basis weight for fabrics, especially in a new product development process.

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Mathematical modeling and simulation of multi-focus image fusion techniques using the effect of image enhancement criteria: a systematic review and performance evaluation

Choudhary

Sethi

2023

Artif Intell Rev

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Structural characterization and measurement of nonwoven fabrics based on multi-focus image fusion

Cited by 16 publications

References 15 publications

Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

Algorithm to determine local basis weight of random fibrous networks with X-ray microtomography and SEM images

Mathematical modeling and simulation of multi-focus image fusion techniques using the effect of image enhancement criteria: a systematic review and performance evaluation

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