Multi-perspective measurement of yarn hairiness using mirrored images

Most photoelectric and imaging methods for yarn hairiness measurements often provide underestimated data of hairy fibers measured from light projection, which ignores the spatial orientations and shapes of protruding fibers. In this project, a three-dimensional (3D) system was developed to detect hairy fibers from multiple perspectives and to reconstruct a 3D model for the yarn that permits fibers to be traced spatially. The system utilized two angled planar mirrors to view a yarn from five different perspectives simultaneously, and a digital camera to capture the multiple images in one panoramic picture. The image-processing techniques were used to dissect the panoramic picture into five sub-images containing separate views of the yarn, and to segment the sub-images to obtain yarn silhouettes showing the edges of the yarn and hairy fibers. A 3D model of the yarn could be built by merging the five silhouettes with the angles defined by the scene geometry of the dual mirrors. From the 3D model, hairy fibers protruding from the yarn core could be traced in the space for accurate length measurements. The system represents a simple and practical solution for the 3D measurement of yarn hairiness.