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

|View full text |Cite

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

Zijun Qiu,

Jingan Wang,

Weidong Gao

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

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

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.

show abstract

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

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

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

Contact Info

Product

Resources

About