A Study on Multi-Focus Images Fusion Technology Based on Fiber Natural Boundaries

Xu, Xin; Wang, Rong Wu

doi:10.4028/www.scientific.net/amr.900.547

AMR

2014

DOI: 10.4028/www.scientific.net/amr.900.547

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A Study on Multi-Focus Images Fusion Technology Based on Fiber Natural Boundaries

Xin Xu

Rong Wu Wang

Abstract: It is difficult to capture a completely clear image of nonwoven web which is thicker than the depth of field of a light microscope. This phenomenon will leads to the data loss and the test error. In this paper, a region-based image fusion algorithm based on fibers natural boundaries was proposed. First, the one-pixel-wide boundaries were extracted from the point-based image fusion process. Then, the image fusion regions were formed by the sharpness diffusion from the source points which have the highest sharpn… Show more

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Cited by 3 publications

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“…In the recent literature, we have found the application of image processing technology by some scholars [7][8][9] to describe the structure of nonwovens, particularly the scanning electron microscope (SEM), 10 the digital volumetric imaging (DVI) micro-imager, 11 computer tomography (CT), 12,13 and the optical microscope (OM). 14,15 However, these methods cannot reconstruct the internal longitudinal structure of nonwovens completely or in a systematic way.…”

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An improved algorithm for three-dimensional reconstruction of nonwoven microstructures by using multi-focus images

Zhang

et al. 2022

Textile Research Journal

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The filtration performance of nonwovens, such as virus protection and air purification, depends largely on their microstructure, that is, their internal structure. With the development of manufacturing techniques, nonwovens can be produced with complex microstructures to deliver low air resistance and high filtration efficiency. Therefore, it seems important to reconstruct an accurate three-dimensional (3D) model to describe the various microstructures for performance evaluation and product development. Multi-focus image fusion is one of the most effective ways used for the 3D nonwoven reconstruction. However, the overlapping and crossing of fibers in multi-focus images taken on an optional microscope make 3D fiber reconstruction incomplete and discontinuous. In this study, we developed a novel fiber segmentation and 3D nonwoven reconstruction algorithm to restore fiber continuity. The fiber web image was firstly thinned into the fiber mid-axis or skeleton, and fiber fragments were detected by searching the intersections. The features, such as the angle and depth, of each fiber fragment were obtained using Harris corner detection. A cluster technique was used to group the head-points of the fiber fragments that have similar features into one cluster. All fiber fragments in the same cluster are fitted with a polynomial curve to form a complete fiber in the 3D space. The experimental results show that this new method is suitable for the reconstruction of nonwovens with complex structures, such as fiber bonding or crossing, and can automatically detect and connect fiber fragments in 3D space. It provides an effective way for the subsequent simulation/evaluation of filtration characteristics.

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confidence: 99%

An improved algorithm for three-dimensional reconstruction of nonwoven microstructures by using multi-focus images

Zhang

et al. 2022

Textile Research Journal

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“…However, newly developed algorithms are also continually appearing and used for multi-focus image fusion, such as Discrete cosine transform (DCT), 14 Nonsubsampled contourlet transform (NSCT), 15 and Region-based image fusion algorithm. 16–18…”

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A novel multi-focus image fusion method of nonwovens based on GHM multiwavelet transform technology

Chen

Deng

Xin

et al. 2018

Textile Research Journal

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In the digital optical microscope, the depth of field is limited in the image acquisition of nonwoven fabrics. The image of the fabric under the single focus image cannot achieve a uniform focus in the whole field of vision, which leads to the blurring of some regions. A new method of multi-focus image fusion based on the Geronimo-Hardin-Massopust (GHM) multiwavelet transform is introduced in this article, which realizes the digital image fusion of a sequence of images taken at different focus settings to achieve a clearer focus fusion of the fiber mesh showing the full field of view within a single image. In this article, a self-built nonwovens micro imaging system is used to collect the image sequence of the fabric at different focus images, and the initial image sequence is processed by critical sampling prefiltering. The high and low frequency components of the image are processed by different fusion rules, and the fusion image of the initial fabric is obtained through the fusion of multiwavelets and inverse transformation. Then, the fusion image of the initial fabric and the subsequent focus image are fused, using the above method, and all the fiber areas after the fusion can be clearly shown to end the operating. Experiments show that the fusion method can solve the difficulty of accurate focusing in a single image with full field of vision.

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

et al. 2019

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A Study on Multi-Focus Images Fusion Technology Based on Fiber Natural Boundaries

Cited by 3 publications

References 5 publications

An improved algorithm for three-dimensional reconstruction of nonwoven microstructures by using multi-focus images

An improved algorithm for three-dimensional reconstruction of nonwoven microstructures by using multi-focus images

A novel multi-focus image fusion method of nonwovens based on GHM multiwavelet transform technology

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

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