Defect Analysis of Textiles Using Artificial Neural Network
Subrata Das,
Amitabh Wahi,
Keerthika S and
Thulasiram N
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Subrata Das: Department of Fashion Technology, Bannari Amman Institute of Technology, India
Amitabh Wahi: Department of Information Technology, Bannari Amman Institute of Technology, India
Keerthika S: Department of Fashion Technology, Bannari Amman Institute of Technology, India
Thulasiram N: Department of Fashion Technology, Bannari Amman Institute of Technology, India
Current Trends in Fashion Technology & Textile Engineering, 2020, vol. 6, issue 1, 1-5
Abstract:
Textile defect detection by application of supervised neural network trained on back error propagation algorithm is presented in this paper. The detection process consists of two parts. First is the conversion of coloured image into RGB components and extraction of features from each colour components. In the second part feed forward, artificial neural network was trained and tested on features obtained above. The trained neural classifier was tested on test dataset. The value of 80% classification accuracy was obtained on test dataset.
Keywords: fashion technology trends; fashion technology advances; fashion and technology articles; fashion technology books pdf; textile science engineering journal; textile science; open access; juniper publishres; high impact journals; online journals publishers; open access journals list (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:adp:ctftte:v:6:y:2020:i:1:p:1-5
DOI: 10.19080/CTFTTE.2020.06.555677
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