An algorithm for online detection of colour differences in warp knitted fabrics

Abstract

The current color difference online detection algorithm has poor real-time performance. The noise affects color difference monitoring and sampling detection results are different from online detection. Therefore, a color difference online detection algorithm is studied. Firstly, the Flat Field and Perfect Reflector Method (PRM) are used to correct the color illumination uniformity of warp knitted fabric images. The image pyramid principle is used to down-sample the images to improve the online detection speed. Secondly, the principle of the histogram intersection method is used to pre-judge the color difference of warp knitted fabric image, and judge whether there is a color difference. The improved K-means algorithm is used to analyze the color types of the fabric, and the $\mathit{CMC}(l:c)$ calculation formula is used to quantitatively calculate the color difference value. Finally, the algorithm has been verified in the factory. The speed of fabric inspection using the algorithm can reach 0.75–0.8m/s, and the color difference detection algorithm is compared with manual detection. The results show that the method can meet the real-time requirements of the system and it is consistent with the sampling test, and the detection speed increased from 0.2 $\mathrm{m}/\mathrm{s}$ to 0.8 $\mathrm{m}/\mathrm{s}.$

KEYWORDS:

• Color difference detection
• image pyramid
• histogram intersection method
• K-means

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of the article: This work was supported by the National Key Research and Development Project (grant number 2018YFB1308800)