Quantitative analysis of blended textiles is important for manufacturers, retailers, and independent testing labs. In ours research, an automatic system for identifying ramie and cotton fibers in the longitudinal view was designed to substitute the manual examination, and a method that can automatically capture well-focused fiber images is proposed.So far, there have been many studies on fiber properties based on longitudinal fiber images, such as the evaluation of fineness and maturity of cottons [1], the identification of convolutions in cotton fibers [2], and the measurement of fiber length [3]. 1To take longitudinal measurements, fibers are usually cut into short segments and spread on a glass slide. A mass of the fiber segments is located at different positions on the sample slide. Up to now, sequential capturing has still served as a conventional fiber image capturing method [1].Abstract This paper introduces a new fiber imaging system that can automatically capture a series of microscopic fiber images in the longitudinal view to form a panoramic image of long-fiber segments for reliable identifications of blended fibers. The panoramic image shows thumbnails of long fibers without missing or duplicating any segments on the sample slide. Firstly, the sample slide is scanned quickly in the X-and Y-axes to capture sequential images of fibers and to register the locations of each image. Secondly, a panoramic image is formed by stitching the sub-images together according to their positions. Thirdly, the panoramic image is analyzed to calculate the skeletons of long-fiber segments, which provide simple representations of fiber shapes and locations, and to register the locations of individual segments for the second scan of the slide. Finally, the triaxial motorized stage transports the slide to the location of each registered segment, readjusts the focus, and captures high quality images for the formal analysis. The entire capturing process is fully automated, and the panoramic view permits efficient image capturing for the reliable identification of ramie and cotton mixed fibers.

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Based on the analysis of stripes on fiber surfaces, a new method for cotton and ramie fiber identification is introduced in this paper. The stripes of a fiber surface were extracted by segmentation, edge detection, and thinning, and then they were orthogonally projected along the curving skeleton of the fiber. In addition, six characteristic parameters for identification were obtained, and based on the method of maximum probability, equations for identification were established on the six probability distribution curves of the characteristic parameters. Finally, weight coefficients of the equations were obtained from self-adapting identification tests. The experiments showed that the overall tolerance for false identification of cotton or ramie fiber was under 7%.

Purpose – Smooth appearance of fabrics after ironing with steam, soleplate, ironing speed and their interactions cannot be studied using household ironing machines such as hang steamer and flatiron. The purpose of this paper is to present the design and verification of a simple, low-cost test platform based on the fabric materials hang-ironing factors includes temperature, humidity, ironing speed (time). Design/methodology/approach – This platform achieves adjustable and stable steam flow rate, enabling any ironing speed and any temperature of soleplate below 200°C. Moreover, the whole ironing process is automatically after experiment level set ahead for better observation to the ironing process. Findings – Regression results of the apparatus are stable, statistical significant which is verified by the statistics under design of experiment. Originality/value – It is useful in other aspects such as nozzle test and improvement, new products evaluation and smooth appearance level experiment and test for new ironing product and its research. It is also useful in other aspects such as nozzle test and improvement, new products evaluation and smooth appearance level experiment and test for new ironing product and its research.

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