Yarn hairiness is one of the essential parameters for assessing yarn quality. Most photoelectric yarn measurement systems are likely to underestimate hairiness because hairy fibers on a yarn surface are often projected or occluded in these two-dimensional (2D) systems. This paper presents a three-dimension (3D) test method for hairiness measurement using a multi-perspective imaging system. The system was developed to reconstruct a 3D yarn model for tracing the actual length of hairy fibers on a yarn surface. Five views of a yarn from different perspectives were created by two angled mirrors, and simultaneously captured in one panoramic picture by a camera. A 3D model was built by extracting the yarn silhouettes in the five views separating and transferring the silhouettes into a common coordinate system. From the 3D model, curved hair fibers were traced spatially so that projection and occlusion occurred in the current systems could be avoided. In the experiment, the proposed method was compared with two commercial instruments, i.e., the Uster Tester and Zweigle Tester. It is demonstrated that the length distribution of hairy fibers measured from the 3D model showed an exponential growth when the fiber length is sorted from shortest to longest. The H-value and S3 value measured by the multi-perspective method are larger than those obtained from Uster Tester and Zweigle Tester, respectively. The H-values of the proposed method have high consistency with those of Uster Tester (r = 0.992). It is indicated that the proposed method allows more accurate and comprehensive hairiness index measurement.
Lei Wang, Bugao Xu, and Weidong Gao, "3D measurement of yarn hairiness via multi-perspective images," Proc. SPIE 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V, 1067916 (Presented at SPIE Photonics Europe: April 26, 2018; Published: 26 July 2018); https://doi.org/10.1117/12.2307844.
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