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The Application of Computer Vision in Cultural Production Innovation

CCD technology is used in production process of cultural products to detect flatness, which reduces the error formation probability. This paper proposes an image detection model for cultural production flatness measurement based on computer vision feature point matching algorithm. The method uses th... Full description

Journal Title: Applied Mechanics and Materials 2014-02-06, Vol.513-517 (Applied Science, Materials Science and Information Technologies in Industry), p.4119-4122
Main Author: Zhu, Xu
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: Zurich: Trans Tech Publications Ltd
ID: ISSN: 1660-9336
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title: The Application of Computer Vision in Cultural Production Innovation
format: Article
creator:
  • Zhu, Xu
subjects:
  • Algorithms
  • Computer vision
  • Error detection
  • Feature extraction
  • Flatness
  • Image detection
  • Matching
  • Pixels
ispartof: Applied Mechanics and Materials, 2014-02-06, Vol.513-517 (Applied Science, Materials Science and Information Technologies in Industry), p.4119-4122
description: CCD technology is used in production process of cultural products to detect flatness, which reduces the error formation probability. This paper proposes an image detection model for cultural production flatness measurement based on computer vision feature point matching algorithm. The method uses the pixel frequency sorting method to divide pixel level of collected images, so as to obtain high precision pixel characteristics as the basis for measuring the flatness for cultural products' structure, and extracts image features of cultural products and carries out matching process to establish an image detection model for flatness measurement. The experimental results show that the proposed algorithm greatly improves the accuracy of flatness measurement for cultural product structure.
language: eng
source:
identifier: ISSN: 1660-9336
fulltext: no_fulltext
issn:
  • 1660-9336
  • 1662-7482
  • 1662-7482
url: Link


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descriptionCCD technology is used in production process of cultural products to detect flatness, which reduces the error formation probability. This paper proposes an image detection model for cultural production flatness measurement based on computer vision feature point matching algorithm. The method uses the pixel frequency sorting method to divide pixel level of collected images, so as to obtain high precision pixel characteristics as the basis for measuring the flatness for cultural products' structure, and extracts image features of cultural products and carries out matching process to establish an image detection model for flatness measurement. The experimental results show that the proposed algorithm greatly improves the accuracy of flatness measurement for cultural product structure.
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subjectAlgorithms ; Computer vision ; Error detection ; Feature extraction ; Flatness ; Image detection ; Matching ; Pixels
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descriptionCCD technology is used in production process of cultural products to detect flatness, which reduces the error formation probability. This paper proposes an image detection model for cultural production flatness measurement based on computer vision feature point matching algorithm. The method uses the pixel frequency sorting method to divide pixel level of collected images, so as to obtain high precision pixel characteristics as the basis for measuring the flatness for cultural products' structure, and extracts image features of cultural products and carries out matching process to establish an image detection model for flatness measurement. The experimental results show that the proposed algorithm greatly improves the accuracy of flatness measurement for cultural product structure.
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notesSelected, peer reviewed papers from the 2014 International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI 2014), January 11-12, 2014, Xi’an, China
abstractCCD technology is used in production process of cultural products to detect flatness, which reduces the error formation probability. This paper proposes an image detection model for cultural production flatness measurement based on computer vision feature point matching algorithm. The method uses the pixel frequency sorting method to divide pixel level of collected images, so as to obtain high precision pixel characteristics as the basis for measuring the flatness for cultural products' structure, and extracts image features of cultural products and carries out matching process to establish an image detection model for flatness measurement. The experimental results show that the proposed algorithm greatly improves the accuracy of flatness measurement for cultural product structure.
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