The Evaluation of Uster Hairiness Results with an Image Analysis Approach

In this study, the images of the yarns were taken using a stereomicroscope. MATLAB software was used in image processing studies. The recommended image acquisition and processing steps in previous studies were followed, and the obtained results from textural parameters of images were compared with the results of Uster H and sh. The highest correlation in Uster H hairiness was obtained in the entropy textural parameter of the Sobel technique. The highest correlation in Uster sh hairiness was obtained in the mean of matrix elements (mean2) from the textural parameters in the Sobel technique. In general, higher correlation results were found in Uster sh than in Uster H. It has been observed that the Uster H results have deficiencies in determining the hairiness of dyed yarns. The different from the literature, this study presents that among the hairiness parameters, Uster sh shows the values closest to the real.

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The Comparison of the Edge Detection Methods in the Determination of Yarn Hairiness through Image Processing

The resolution, quality and speed of the cameras have improved enormously in recent years. The combination of camera advancements and the software industry offers significant opportunities. 

In this study, an image processing approach for the determination of yarn hairiness was presented. Yarn images taken under a microscope were examined in MATLAB software. 

Seven different edge detection algorithms were used in order to separate the hairs from the yarn body. Seven different textural properties of obtained yarn images were compared with Zweigle hairiness test results. The findings have indicated that yarn hairiness can be clearly detected from microscope images with a six-step algorithm. 

The first four phases are grayscale, double format, 2D median filtering and histogram-fitting, respectively. The fifth stage is the edge detection algorithm and the sixth stage is the use of textural parameters. When compared with the Zweigle hairiness results, the most obvious finding to emerge from this study is that the best appropriate technique for edge detection was the Sobel method, and the textural parameter to be used in the evaluation was the standard deviation of matrix elements.

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