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第24届中国控制与决策会议

作者： Ling Ouyang 1 , Hongtao Peng 2 , Dongyun Wang 3 ,Yongping Dan 4 , Fanghua Liu 5 1, 2, 3, 4, 5. School of Electrical and Information, Zhongyuan University of Technology, Zhengzhou 450007

foreign fibers accounted for a small proportion in cotton, but there is serious impact on the quality of textile. foreign fibers are removed by hand, which is low efficiency. Generally, the methods of fixed threshold are used to identify foreign fibers in cotton, but high speed flow of cotton is easy to result in fluctuations on light, the color of captured images will be changed accordingly, then misidentification possibility will be increased. But the suitable amount of sample libraries are used in the identification algorithm of supervised classification, which eliminate this defect to meet the requirements of accuracy and real-time. In this paper, according to the character of image gray of foreign fibers in cotton, and mathematical model is established. Further, important image features are enhanced by image processing, foreign fibers’ characters are drawn. At last, Euclidean distance and k-nearest neighbor classification are adopted in identification algorithm, and finally foreign fibers are identified.

关键词： foreign fibers identification Euclidean distance k-nearest neighbor classification algorithm

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Classification and identification of foreign fibers in cotton on the basis of a support vector machine

Classification and identification of foreign fibers in cotto...

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第三届国际计算机及计算技术农业应用学术会议

作者： Ronghua Ji~a,Daoliang Li~(a,*),Lairong Chen~b,Wenzhu Yang~a a College of Information and Electronic Engineering,China Agricultural University,Beijing,100083,China b School of Technology,Beijing Forestry University,Beijing,100083,China

foreign fibers in cotton have seriously affected the quality of cotton *** classification and identification of foreign fibers in cotton is the foundation of cotton foreign fiber automated *** paper takes the typical cotton foreign fibers in China’s textile enterprises as the research object,and acquires the images under simulated actual cotton *** various classification features are calculated and *** results show that aspect ratio,roundness,duty cycle and I are the effective features for classifying various foreign *** paper puts forward a classifier of cotton foreign fibers based on a support vector machine.A Decision Tree Support Vector Machine(DTSVM) can not only avoid the non-separated region,but also improve the training speed while the training sample number gradually decreases,going through the decision *** DTSVM is to be used to identify the sorts of common foreign fibers in *** experimental data set shows that the rates of identifying different kinds of foreign fibers are greater than 92% using the proposed DTSVM.

关键词： Cotton foreign fibers Classification features Support vector machine

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Fast processing of foreign fiber images by image blocking

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Information Processing in Agriculture 2014年第1期1卷 2-13页

作者： Yutao Wu Daoliang Li Zhenbo Li Wenzhu Yang Beijing Engineering&Technology Research Center for Internet of Things in Agriculture China-EU Center for Information and Communication Technologies in Agriculture of China Agriculture UniversityBeijing100083PR China Key Lab of Machine Learning and Computational Intelligence College of Mathematics and Computer ScienceHebei UniversityBaoding071002PR China

In the textile industry,it is always the case that cotton products are constitutive of many types of foreign fibers which affect the overall quality of cotton *** the foundation of the foreign fiber automated inspection,image process exerts a critical impact on the process of foreign fiber *** paper presents a new approach for the fast processing of foreign fiber *** approach includes five main steps,image block,image predecision,image background extraction,image enhancement and segmentation,and image *** first,the captured color images were transformed into gray-scale images;followed by the inversion of gray-scale of the transformed images;then the whole image was divided into several ***,the subsequent step is to judge which image block contains the target foreign fiber image through image *** we segment the image block via OSTU which possibly contains target images after background eradication and image ***,we connect those relevant segmented image blocks to get an intact and clear foreign fiber target *** experimental result shows that this method of segmentation has the advantage of accuracy and speed over the other segmentation *** the other hand,this method also connects the target image that produce fractures therefore getting an intact and clear foreign fiber target image.

关键词： Cotton foreign fibers Fast image processing Image block Image pre-decision Image connection

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