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A precise method of color space conversion in the digital printing process based on PSO-DBN.

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Title: A precise method of color space conversion in the digital printing process based on PSO-DBN.
Authors: Su, Zebin1 (AUTHOR) suzebin@xpu.edu.cn, Yang, Jinkai1 (AUTHOR), Li, Pengfei1 (AUTHOR), Jing, Junfeng1 (AUTHOR), Zhang, Huanhuan1 (AUTHOR)
Source: Textile Research Journal. May2022, Vol. 92 Issue 9/10, p1673-1681. 9p.
Subjects: Digital printing, Particle swarm optimization, Back propagation, Color space
Abstract: Neural networks have been widely used in color space conversion in the digital printing process. The shallow neural network easily obtains the local optimal solution when establishing multi-dimensional nonlinear mapping. In this paper, an improved high-precision deep belief network (DBN) algorithm is proposed to achieve the color space conversion from CMYK to L*a*b*. First, the PANTONE TCX color card is used as sample data, in which the CMYK value of the color block is used as input and the L*a*b* value is used as output; then, the conversion model from CMYK to L*a*b* color space is established by using DBN. To obtain better weight and threshold, DBN is optimized by a particle swarm optimization algorithm. Experimental results show that the proposed method has the highest conversion accuracy compared with Back Propagation Neural Network, Generalized Regression Neural Network, and traditional DBN color space conversion methods. It can also adapt to the actual production demand of color management in digital printing. [ABSTRACT FROM AUTHOR]
Copyright of Textile Research Journal is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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  Data: A precise method of color space conversion in the digital printing process based on PSO-DBN.
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  Data: <searchLink fieldCode="AR" term="%22Su%2C+Zebin%22">Su, Zebin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> suzebin@xpu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Jinkai%22">Yang, Jinkai</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Pengfei%22">Li, Pengfei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jing%2C+Junfeng%22">Jing, Junfeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Huanhuan%22">Zhang, Huanhuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Textile+Research+Journal%22">Textile Research Journal</searchLink>. May2022, Vol. 92 Issue 9/10, p1673-1681. 9p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Digital+printing%22">Digital printing</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Back+propagation%22">Back propagation</searchLink><br /><searchLink fieldCode="DE" term="%22Color+space%22">Color space</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Neural networks have been widely used in color space conversion in the digital printing process. The shallow neural network easily obtains the local optimal solution when establishing multi-dimensional nonlinear mapping. In this paper, an improved high-precision deep belief network (DBN) algorithm is proposed to achieve the color space conversion from CMYK to L*a*b*. First, the PANTONE TCX color card is used as sample data, in which the CMYK value of the color block is used as input and the L*a*b* value is used as output; then, the conversion model from CMYK to L*a*b* color space is established by using DBN. To obtain better weight and threshold, DBN is optimized by a particle swarm optimization algorithm. Experimental results show that the proposed method has the highest conversion accuracy compared with Back Propagation Neural Network, Generalized Regression Neural Network, and traditional DBN color space conversion methods. It can also adapt to the actual production demand of color management in digital printing. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Textile Research Journal is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/00405175211067287
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 1673
    Subjects:
      – SubjectFull: Digital printing
        Type: general
      – SubjectFull: Particle swarm optimization
        Type: general
      – SubjectFull: Back propagation
        Type: general
      – SubjectFull: Color space
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            NameFull: Yang, Jinkai
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            NameFull: Li, Pengfei
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            – D: 01
              M: 05
              Text: May2022
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              Y: 2022
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