Study On Image Detection Technique Of Yarn Hairiness

Yarn hairiness not only affects the efficiency of subsequent processing and the quality of cloth, but also causes environmental pollution and affects normal operation of machine,does damage harm to human health. Therefore, yarn hairiness detection is an important step in textile production and processing. At present, hairiness testing methods mainly are the blackboard method testing and photoelectric method in the world. By blackboard methodtesting, yarn are wrapped on the blackboard in a certain method and then compared with the standard sample.The inspecting speed is slow,and only processes eyes comparing may produce visual error. Hairness can generated reflection light and scattering light by the parallel beam,which can changes electrical signals in measuring, photoelectric method measure hairiness characteristic parameters of each set length, can not test non whole millimeter level,so it is not enough to the measuring. On the basis of the Barella and Chimeh M’s researches, visual testing technology of yarn hairiness can effectively avoid shortcomings of the above methods, improve the level of yarn hairiness testing.On the basis of the traditional photoelectric method, this topic considers fully the characteristics and properties of yarn hairiness, applying uniform motion video cameras to record the yarn hairiness, recording yarn hairiness of video image, and upload in the computer. Combined with OpenCV open-source libaray, this testing uses using Visual C + + 2010 programming software, realizes the visualization processing of the video and images.First of all, according to the method of frame skip, we can get a single frame of digital image, then we can process the image: by gray level transformation, histogram equalization,filtering and noise reduction, Canny operator edge extraction, morphological opening operation, etc, to eliminate the effects of background image, and get a clear yarn hairiness image. Then, using Freeman chain code tracking scan of yarn hairiness, we extract the hairiness boundary contour, and convert resolution ratio of digital image and the length of the unit, calculate the output parameters of hairiness,realize the qualitative measurement of hairiness.All the output of processed image and hairiness parameters can be operated by Recycling operation, at a result output the processed hairiness video, realize the visualization of hairiness testing. This topic also test time of all the process,to obtain. Speed is 30m/min.Compared with the national standard, Speed is viable to visualization hairiness testing,can meet the needsBased on the visual detection technology of yarn hairiness the conclusions are that clearly scan outline of the hairiness and output hairiness characteristic parameters, intuitively display and compare hairiness video of before and after processing. Visual detection technology has the characteristics of visibility, quick, convenient, which improved the detection method of yarn hairiness.