基于图像处理的血液透析器纤维识别计数
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Recognition and Counting of Blood Dialyzer Fibers Based on Image Processing
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    摘要:

    为获得血液透析膜纤维的高精度识别与计数, 通过对纤维图像颜色聚类特征的实验和分析, 得出在YUV 空间中仅利用颜色分量U 和V 对图像进行颜色聚类. 利用K-means 聚类算法对图像进行颜色聚类, 根据图像中各像素的聚类属性对图像进行分割. 在纤维的识别计数环节, 采用Hough 变换的方式对分割出的纤维图像识别并计数. 实验结果表明, 该算法识别精度高, 鲁棒性好.

    Abstract:

    In order to obtain high-precision fiber identification and counting of fibers by color image analysis and clustering features of the experiment, obtained in the YUV space using only U, V components of the image color clustering. Using k-means clustering algorithm for color image clustering, each pixer according to the image clustering properties of the image segmentation.Identification of the fiber count links, using the segmented Hough transform the way out of the fiber image recognition and counting. Experiments show that the algorithm to identify high precision, can adapt to a range of optical changes in the environment, better robustness.

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曹婧蕾,李军华.基于图像处理的血液透析器纤维识别计数.计算机系统应用,2012,21(10):166-170

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  • 收稿日期:2012-03-05
  • 最后修改日期:2012-04-16
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