Simulation of photosensor-based hairiness measurement using digital image analysis

Abstract

The hair-counting technique using photosensors is a common method to measure the hairiness of the yarns. However, the literature recognizes some deficiencies of the technique regarding the sensor limitations. This paper describes a computer vision approach to simulate the photosensors and to investigate the parameters effecting the hairiness measurement when using these sensors. An algorithm developed to simulate the photosensor signals is explained. The effects of sensor resolution, signal threshold level and selection of zero reference positions from the core are investigated. The correlation between the measurements taken from two different sides of the yarn core is also examined. Twenty yarn samples are tested using a Zweigle G565 hairiness tester, and the results are compared with the hairiness measurements from the simulated photosensor system using digital images.

Key Words:

• Yarn hairiness
• digital image analysis
• sensor resolution

ACKNOWLEDGMENTS

This project has been sponsored by Loughborough University's School of Mechanical and Manufacturing Engineering. We also would like to thank both the Textile Engineering Department of Istanbul Technical University for providing the yarn samples and North Carolina State University's College of Textiles for enabling the use of yarn-testing facilities.