| 基于模糊均值聚类和亮度均衡的钢管自适应计数 |
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| 引用本文： | 刘景波,金炜东. 基于模糊均值聚类和亮度均衡的钢管自适应计数[J]. 激光与光电子学进展, 2010, 0(1) |
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| 作者姓名： | 刘景波 金炜东 |
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| 作者单位： | 西南交通大学电气工程学院; |
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| 摘 要： | 针对现有计数方法的缺陷,根据钢管截面区域与背景图像存在较大亮度差异的特点,提出了基于模糊C均值(FCM)聚类和亮度均衡的钢管自适应计数方法。用亮度均衡等方法对钢管图像进行预处理,降低图像中高光和阴影等的不良影响;利用FCM聚类方法自适应分割图像;对二值图像进行连通区域标记,获取区域几何特征;利用统计学方法和FCM聚类方法剔除非钢管截面区域,统计计数。实验表明,新方法不仅计数速度快,而且计数精度高,同时具有对不同环境条件的自适应性。
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| 关 键 词： | 图像处理 钢管计数 模糊C均值聚类 亮度均衡 |
Steel Pipe Adaptive Counting Based on Fuzzy Means Clustering and Intensity Balancing |
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| Liu Jingbo Jin Weidong. Steel Pipe Adaptive Counting Based on Fuzzy Means Clustering and Intensity Balancing[J]. Laser & Optoelectronics Progress, 2010, 0(1) |
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| Authors: | Liu Jingbo Jin Weidong |
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| Affiliation: | School of Electrical Engineering;Southwest Jiaotong University;Chengdu;Sichuan 610031;China |
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| Abstract: | Aiming at the shortcoming of existing counting methods,a new method based on fuzzy C-means(FCM) clustering and intensity balancing is proposed for steel pipe adaptive counting,according to that there is a big luminance difference between pipe cross-section area and background image.Firstly,the image of the steel pipe is adjusted and balanced for reducing the adverse effect of highlights and shadows in the image;secondly,the image is segmented by using FCM clustering;thirdly,the binary image is labeled with ... |
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| Keywords: | image processing steel pipe counting fuzzy C-means clustering intensity balancing |
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