An efficient method for solid‐colour and multicolour region segmentation in real yarn‐dyed fabric images

Luo, Lin; Shen, Hui Liang; Shao, Si Jie; Xin, John Haozhong

doi:10.1111/cote.12131

Cited by 12 publications

(17 citation statements)

References 23 publications

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“…Akin to the reflection model of a yarn dyed fabric proposed by Luo and co-workers [1,8], both light emitted from light source of measurement system (the red arrow in Fig. 2, E D ) and reflected by neighboring yarns (the blue arrow in Fig.…”

Section: Reflection Model Of Yarn Windingsmentioning

confidence: 94%

“…As shown in Fig. 4, the irradiance at pixel p C ; q C of the image plane of the system, is given [8]:…”

Section: Spectral Response Of Msi Systems To a Single Strand Of Yarnmentioning

confidence: 99%

“…The reflectance of single strand of yarn samples was acquired by a MSI system ICM [2,[8][9][10]]. The ICM system employed a circular light source, which can reduce the influence of specular light on samples.…”

Section: A Sample Preparationmentioning

confidence: 99%

“…Luo and co-workers [2,8,9] applied a MSI system, namely imaging color measurement (ICM), to acquire the yarn color of a yarn dyed fabric. The multispectral images of a yarn dyed fabric were first partitioned into dominant color regions by a Gaussian model [2].…”

Section: Introductionmentioning

confidence: 99%

“…The multispectral images of a yarn dyed fabric were first partitioned into dominant color regions by a Gaussian model [2]. Second, the solid-color fabric regions were distinguished from multicolor fabric regions in terms of CIExyY histogram distributions [8]. Finally, weft and warp yarns in a multicolor region were segmented by a modified K-means clustering in the CIExyY space [9].…”

Section: Introductionmentioning

confidence: 99%

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Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns

et al. 2015

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The state-of-the-art multispectral imaging system can directly acquire the reflectance of a single strand of yarn that is impossible for traditional spectrophotometers. Instead, the spectrophotometric reflectance of a yarn winding, which is constituted by yarns wound on a background card, is regarded as the yarn reflectance in textile. While multispectral imaging systems and spectrophotometers can be separately used to acquire the reflectance of a single strand of yarn and corresponding yarn winding, the quantitative relationship between them is not yet known. In this paper, the relationship is established based on models that describe the spectral response of a spectrophotometer to a yarn winding and that of a multispectral imaging system to a single strand of yarn. The reflectance matching function from a single strand of yarn to corresponding yarn winding is derived to be a second degree polynomial function, which coefficients are the solutions of a constrained nonlinear optimization problem. Experiments on 100 pairs of samples show that the proposed approach can reduce the color difference between yarn windings and single strands of yarns from 2.449 to 1.082 CIEDE2000 units. The coefficients of the optimal reflection matching function imply that the reflectance of a yarn winding measured by a spectrophotometer consists of not only the intrinsic reflectance of yarn but also the nonignorable interreflection component between yarns.

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Section: Reflection Model Of Yarn Windingsmentioning

confidence: 94%

“…As shown in Fig. 4, the irradiance at pixel p C ; q C of the image plane of the system, is given [8]:…”

Section: Spectral Response Of Msi Systems To a Single Strand Of Yarnmentioning

confidence: 99%

Section: A Sample Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns

et al. 2015

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Color specification of a single strand of yarn from a multispectral image

Luo

Shen

Shao

et al. 2015

Color Research & Application

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Many applications in textile require color measurement of single strands of yarns due to unavailability of a mass of consecutive yarns. While multispectral imaging systems can capture images of single strands of yarns, an unavoidable problem accompanied is how to specify their colors from images, in which pixel values vary with positions owing to three‐dimensional shape of yarn. Based on the response of multispectral imaging systems to single strands of yarns, this article formulates the color specification problem as an optimization question and four methods are proposed: average of all pixels (AA), average of pixels in central area (AC), maxima of all pixels (MA), and lightness weighting method (LW). The first experiment analyzed color distribution of pixels on a single strand of yarn. Experimental results show pixels in central area have smallest color variation and largest intensity. The second experiment compared the proposed methods. Results show that CIEXYZ, L*, and C* values specified by the AA and MA methods are lowest and highest. Finally, colors of single strands of yarns specified by the proposed methods were compared with spectrophotometric colors of yarn windings using 12 pairs of single strands of yarns and yarn windings. Experimental results show the MA method yields the smallest lightness and chroma difference compared with spectrophotometric colors of yarn windings. The average color difference between spectrophotometric colors of yarn windings and multispectral imaging colors of single strands of yarns specified by the AA, AC, MA, and LW methods is 3.45, 2.72, 2.37, and 3.33 CMC(2:1) units. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 500–512, 2016

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Color pattern recognition for yarn‐dyed fabrics

Zheng

Wang

Zhou³

et al. 2018

Color Research & Application

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In the process of designing and analyzing the yarn‐dyed fabric, the yarn color pattern has an important effect on the appearance of the fabric. An automatic color pattern recognition method for yarn‐dyed fabric is proposed in this study. The proposed method uses the fabric images obtained from a high‐resolution digital camera image acquisition system. The local statistical texture features are used for yarn texture segmentation. The yarn color classification problem is then formulated in a research framework of multiregion fuzzy segmentation, which can be added auxiliary variables and solved efficiently by the fast dual projection algorithm. The color values of the yarn crossing points are calculated by the yarn color classification results. The locations of the yarn crossing points are detected by a lightness gradient projection method. Different kinds of fabrics are tested in the experiments. Experiments on 14 actual fabrics show that the approach proposed in this study is effective for classifying yarn color and extracting the yarn color pattern in yarn‐dyed fabric.

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An efficient method for solid‐colour and multicolour region segmentation in real yarn‐dyed fabric images

Cited by 12 publications

References 23 publications

Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns

Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns

Color specification of a single strand of yarn from a multispectral image

Color pattern recognition for yarn‐dyed fabrics

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