A Computer-Vision-Based Nondestructive Hairiness Measurement System on Yarn Cone Transportation Line

Qiu, Zijun; Wang, Jingan; Gao, Weidong

doi:10.1109/tim.2024.3372208

IEEE Trans. Instrum. Meas.

2024

DOI: 10.1109/tim.2024.3372208

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A Computer-Vision-Based Nondestructive Hairiness Measurement System on Yarn Cone Transportation Line

Zijun Qiu,

Jingan Wang,

Weidong Gao

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Yarn hairiness measurement based on multi-camera system and perspective maximization model

Cao,

Chen,

et al. 2024

J. Electron. Imag.

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Accurate measurement and identification of the number and length of yarn hairiness is crucial for spinning process optimization and product quality control. However, the existing methods have problems, such as low detection accuracy and efficiency, and incomplete detection. In order to overcome the above defects, an image acquisition device based on a multi-camera system is established to accurately obtain multiple perspectives of hairiness images. An automatic threshold segmentation method based on the local bimodal is proposed based on image difference, convolution kernel enhancement, and histogram equalization. Then, the clear and unbroken yarn hairiness segmentation images are obtained according to the hairiness edge extraction method. Finally, a perspective maximization model is proposed to realize the calculation of the hairiness H value and the number of hairiness in interval. Six kinds of cotton ring-spun yarn with different linear densities are tested using the proposed method, YG133B/M instrument, manual method, and single perspective method. The results show that the proposed multi-camera method can realize the index measurement of the yarn hairiness.

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Yarn hairiness measurement based on multi-camera system and perspective maximization model

Cao,

Chen,

et al. 2024

J. Electron. Imag.

View full text Add to dashboard Cite

show abstract

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A Computer-Vision-Based Nondestructive Hairiness Measurement System on Yarn Cone Transportation Line

Cited by 1 publication

References 26 publications

Yarn hairiness measurement based on multi-camera system and perspective maximization model

Yarn hairiness measurement based on multi-camera system and perspective maximization model

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