3D Measurement of Yarn Unevenness Based on A Low-Cost Multi-Camera Collaborative System and Signal Analysis

The quality of the yarn directly determines the performance of the fabric. Existing methods lack three-dimensional rapid evaluation of yarn quality. To overcome the above problem, this paper designs a low-cost multi-camera collaborative system to simultaneously and accurately capture the same segment of yarn image from different perspectives. Specifically, this study introduces a novel yarn image segmentation method, including Local vertical interruption, Horizontal clearing algorithm, and Morphological operation, to accurately obtain the appearance diameter value of the same yarn segment from four views. Subsequently, a 3D model of yarn core for solving elliptical parameters based on multiple camera positions is established and validated. Then, the elliptical cross-sectional area of the yarn and its equivalent circular diameter are obtained. Four types with the same kind of yarns are tested using the proposed method and Uster Evenness Tester 5. By comparing the short-term, periodic, and long-term variation of yarn core, including the diameter value, three-dimensional unevenness coefficient, spectrogram, and variation length curve under different cutting lengths, it is demonstrated that the proposed method is consistent with the Uster measurement results. The experimental results highlight that the proposed method can accurately and effectively evaluate the yarn unevenness.