| 图像测量中平行线的自适应拟合 |
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| 引用本文： | 蒋爱德.图像测量中平行线的自适应拟合[J].计算机系统应用,2014,23(6):175-178. |
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| 作者姓名： | 蒋爱德 |
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| 作者单位： | 河南牧业经济学院 信息工程学院, 郑州 450011 |
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| 摘 要： | 对于图像测量中平行线边缘点的拟合问题，本文通过聚类分析法中的 算法去除边缘点图像中的噪声数据，并结合最小二乘法对平行线边缘点进行分类拟合，解决了传统算法中根据图像特点人为划分区域进行分别拟合的问题，达到了机器对图像进行自动处理的目的.
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| 关 键 词： | 图像测量 最小二乘法 聚类分析 |
| 收稿时间： | 2013/10/7 0:00:00 |
| 修稿时间： | 2013/11/28 0:00:00 |
Parallel Lines Adaptive Fitting in Image Measurement |
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| JIANG Ai-De.Parallel Lines Adaptive Fitting in Image Measurement[J].Computer Systems& Applications,2014,23(6):175-178. |
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| Authors: | JIANG Ai-De |
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| Affiliation: | Department of Information and Engineering, Henan University of Animal Husbandry and Economy, Zhengzhou 450011, China |
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| Abstract: | For the parallel edge points fitting in image measurement, this paper combines with the least square method to classify parallel edge points fitting through clustering analysis algorithm to eliminate the noise in the edge points image. The traditional algorithm based on image characteristics dividing area artificially to fitting respectively is solved. The result achieves the purpose of automatic image processing by machine. |
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| Keywords: | image measurement least squares clustering analysis |
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