ICISP 2016: Image and Signal Processing pp 71-78 | Cite as

Defect Detection on Patterned Fabrics Using Entropy Cues

  • Maricela Martinez-Leon
  • Rocio A. Lizarraga-Morales
  • Carlos Rodriguez-Donate
  • Eduardo Cabal-Yepez
  • Ruth I. Mata-Chavez
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9680)

Abstract

Quality control is an essential step in the textile manufacturing industry. There is a growing interest in the field of automation using computer vision for freeing human beings from the inspection task. In this paper, patterned fabric images are analyzed using entropy cues in order to detect different kinds of defects. In our proposal, we transform the test image to an entropy image in which the defects show low values and can be easily separated by a simple thresholding. Our method is evaluated and compared with previously proposed approaches, showing better results on an extensive database of real defective and non-defective fabrics.

Keywords

Defect detection Fabric Entropy Texture analysis 
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Notes

Acknowledgments

The authors would like to thank Henry Y.T. Ngan from the Industrial Automation Research Laboratory in the Department of Electrical and Electronic Engineering at the University of Hong Kong, for providing the database of fabrics. Martinez-Leon would like to acknowledge for the grant provided by the Mexican National Council of Science and Technology (CONACyT). This research was supported by the PRODEP through the NPTC project with number DSA/103.5/15/7007.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Maricela Martinez-Leon
    • 1
  • Rocio A. Lizarraga-Morales
    • 1
  • Carlos Rodriguez-Donate
    • 1
  • Eduardo Cabal-Yepez
    • 1
  • Ruth I. Mata-Chavez
    • 1
  1. 1.Departamento de Estudios Multidisciplinarios, Division de IngenieriasUniversidad de GuanajautoYuririaMexico

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