In this thesis, A novel method for measuring the evenness of raw silk is introduced. Firstly, the moving raw silk images are captured by image acquisition system including a Charge Coupled Device (CCD) line sensor, a telecentric lens, a light source. Then, the raw silk images are processed sequentially with threshold segmentation, morphological opening operation. Threshold segmentation is used to realize the separation of raw silk and background, morphological opening operation can eliminate the protrusion and the loop fiber which surrounding the main body of raw silk in the binary image. the coefficient of variation (CV value) of diameter is adopted to characterized the raw silk evenness. its suitable performance is illustrated using experimental results.
In this paper, a new yarn appearance measurement system based on machine vision is introduced. The yarn images are continuously captured by image acquisition system. To extract the main body of the yarn accurately, the yarn images are processed sequentially with threshold segmentation and morphological opening operation. Then the coefficient of variation (CV value) of diameter is calculated to characterize the yarn evenness. The measurement process achieves result (CV value) which can be compared with USTER evenness tester by image processing techniques. By comparing different methods which use different algorithms, a suitable method is chosen to be used in this new measurement system. Then a more accurate, more efficient and faster measurement system will meet requirements in the future.
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