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DOI: 10.14569/IJACSA.2017.081133
PDF

FabricVision: System of Error Detection in the Manufacture of Garments

Author 1: Jaime Moreno
Author 2: Arturo Aguila
Author 3: Eduardo Partida
Author 4: Oswaldo Morales
Author 5: Ricardo Tejeida

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 11, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.

Keywords: Computer vision; histogram of oriented gradient; segmentation; object detection; image capture

Jaime Moreno, Arturo Aguila, Eduardo Partida, Oswaldo Morales and Ricardo Tejeida, “FabricVision: System of Error Detection in the Manufacture of Garments” International Journal of Advanced Computer Science and Applications(IJACSA), 8(11), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081133

@article{Moreno2017,
title = {FabricVision: System of Error Detection in the Manufacture of Garments},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081133},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081133},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {11},
author = {Jaime Moreno and Arturo Aguila and Eduardo Partida and Oswaldo Morales and Ricardo Tejeida}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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