An Intelligent Defect Detection Method of Small Sized Ceramic Tile Using Machine Vision

Linjie Yang, Mina Chong, Qiming Li, Jun Li

2018

Abstract

Quality control of small sized ceramic tile is an important part for manufacturing enterprise. To improve the efficiency and precision of ceramic tile defect detection, an intelligent detection method is proposed in this paper. Firstly, the noise is eliminated by image pre-processing，and the geometric primitive of ceramic tile is taken as benchmark. Meanwhile, the nearest neighbor algorithm is adopted to search measurement point, and the size parameters are calculated by Euclidean distance. Then, local defect feature of chromatism is obtained by patch strategy and composite contour mask. It is necessary to merge potential block to recover original appearance of defects. Finally, the optimized parameters from feature distribution and a discriminant function are utilized to achieve target defect detection. The experimental results show that the method has good detection effect and high real-time performance.

Paper Citation

in Harvard Style

Yang L., Chong M., Li Q. and Li J. (2018). An Intelligent Defect Detection Method of Small Sized Ceramic Tile Using Machine Vision.In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 427-433. DOI: 10.5220/0006972104270433

in Bibtex Style

@conference{icectt18,
author={Linjie Yang and Mina Chong and Qiming Li and Jun Li},
title={An Intelligent Defect Detection Method of Small Sized Ceramic Tile Using Machine Vision},
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={427-433},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006972104270433},
isbn={978-989-758-312-4},
}

in EndNote Style

TY - CONF

JO - 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,
TI - An Intelligent Defect Detection Method of Small Sized Ceramic Tile Using Machine Vision
SN - 978-989-758-312-4
AU - Yang L.
AU - Chong M.
AU - Li Q.
AU - Li J.
PY - 2018
SP - 427
EP - 433
DO - 10.5220/0006972104270433