This paper proposes a method to realize computer-aided analysis and reverse reconstruction for the weave pattern of fabric. Firstly, a double-face imaging system is designed to get the redundant image information used to correct node classification, and then the image gridding processing is realized by using the projection algorithm in the warp and weft directions. The grid node color was determined by the color clustering method. Then the attributes and classification of the grid nodes are determined by the analysis of the edge strength information. The correction of node classification is realized with the information of adjacent nodes and the color of the double surface image of the corresponding fabric region. After that, the acquired nodes were encoded with 0 and 1, and then converted into a digital matrix; the basic weave structure matrix of the fabric was derived by matrix transformations. In the meantime, two one-dimensional row and column matrices and a color mapping table are adopted to represent the warp and weft yarn color array. On the basis of the above, the digital files of the woven pattern of sample fabric are established. Finally, the model of the fabric weave pattern can be obtained by the reverse reconstruction method and the automatic recognition of the fabric weave pattern is realized. Through comparison of the original fabric sample image with the reconstructed weave pattern model, it is proved that the proposed method is effective.
机构:
Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
Hwang, Jiyoung
Chung, Myung Jin
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Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
Chung, Myung Jin
Bae, Younga
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Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
Bae, Younga
Shin, Kyung Min
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Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
Shin, Kyung Min
Jeong, Sun Young
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Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
Jeong, Sun Young
Lee, Kyung Soo
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Sungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South KoreaSungkyunkwan Univ, Dept Radiol, Ctr Imaging Sci, Samsung Med Ctr,Sch Med, Seoul 135710, South Korea
机构:
Nanjing Univ, Med Sch, Nanjing 210093, Peoples R China
Nanjing Univ Posts & Telecommun, Sch Integrated Circuit Sci & Engn, Ind Educ Integrat Sch, Nanjing 210023, Peoples R ChinaNanjing Univ, Med Sch, Nanjing 210093, Peoples R China
Fan, Lin
Shen, Yilei
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Nanjing Univ Posts & Telecommun, Sch Integrated Circuit Sci & Engn, Ind Educ Integrat Sch, Nanjing 210023, Peoples R ChinaNanjing Univ, Med Sch, Nanjing 210093, Peoples R China
Shen, Yilei
Lou, Doudou
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Nanjing Inst Food & Drug Control, Nanjing 211198, Peoples R ChinaNanjing Univ, Med Sch, Nanjing 210093, Peoples R China
Lou, Doudou
Gu, Ning
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Nanjing Univ, Med Sch, Nanjing 210093, Peoples R ChinaNanjing Univ, Med Sch, Nanjing 210093, Peoples R China
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Virginia Tech, Ctr High Performance Mfg, Grad Dept Ind & Syst Engn 0118, Blacksburg, VA 24061 USAVirginia Tech, Ctr High Performance Mfg, Grad Dept Ind & Syst Engn 0118, Blacksburg, VA 24061 USA
Creehan, Kevin D.
Bidanda, Bopaya
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Univ Pittsburgh, Dept Ind Engn, Pittsburgh, PA 15261 USAVirginia Tech, Ctr High Performance Mfg, Grad Dept Ind & Syst Engn 0118, Blacksburg, VA 24061 USA