Chan-Vese segmentation model for faster and accurate evaluation of yarn packing density
2016
Eldessouki, Mohamed | Sayed ʾIbrāhim,
Yarn packing density is an important parameter in correlating the internal structure of the yarn to its final properties and performance. The current methods of determining the yarn packing density have three main drawbacks: they are labor dependent, they are time consuming, and they approximate many parameters of the fibers and the yarn. The current work utilizes the Chan-Vese (CV) segmentation model to detect the actual contours of the yarn and the fibers inside its cross-section. This algorithm allows the automation of the process which reduces the time required for the analysis and makes it independent from the human element. The method also avoids the approximations involved in the traditional methods by calculating the actual areas of the fibers and the yarn which makes it more precise in determining the yarn packing density. A user-friendly graphical user interface (GUI) was developed to utilize the CV algorithm and calculate different yarn parameters such as the yarn's radial packing density, the yarn's effective diameter, and the yarn's effective packing density. The area ratio factor (ARF) was used as a quick indicator of the accuracy of fiber segmentation. The CV algorithm was described in detail and tested with ring-spun yarns from different materials and the results were found to be in agreement with the reported values of such yarns. The introduced method can be extended to the evaluation of fibrous materials other than yarns.
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