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计算机科学与应用
Vol. 6 No. 8 (August 2016)
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二次识别算法在工件识别中的应用
The Application of Two-Time Recognition on the Work Piece Detection
DOI:
10.12677/CSA.2016.68060
,
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被引量
下载: 1,750
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作者:
万潇月
*
,
叶桦
*
,
尤卫卫
*
:东南大学自动化学院,江苏 南京
关键词:
工件识别
;
二次识别
;
模板匹配
;
Work Piece Detection
;
Two-Time Recognition
;
Template Matching
摘要:
针对工业流水线上机器视觉系统工件识别的问题,提出了一种有效的基于模板匹配的二次识别算法。在识别之前,根据已知工件建立模板库并对每个模板提取一组特征组合。一次识别采用基于像素点的匹配算法,计算待匹配图像与模板图像的像素点灰度值的整体相似性,作为一次识别系数;二次识别采用基于特征的匹配算法,计算待匹配图像与模板图像的特征区域的细节吻合性,作为二次识别系数。综合两次识别系数,两者之和最大者为最佳匹配结果。实验结果表明,本文的方法简单有效且识别率高。
Abstract:
According to the work piece detection problems based on the machine vision system on the in-dustrial pipeline, an effective two-time recognition algorithm based on template matching is pro-posed. Before recognition, the template library in which each template has a set of features should be established. First, the point matching recognition is used to compare the collected image and all the template images in the library one by one, during which the gray value of the pixels is compared and the first matching coefficient is recorded. Then, the feature matching is used to compare the feature area of the collected image and the templates, and the second coefficient is recorded. The final matching coefficient is added by the first matching coefficient and the second one. The highest matching coefficient will be outputted as the result. The experimental results show that the method is simple and efficient with high accuracy.
文章引用:
万潇月, 叶桦, 尤卫卫. 二次识别算法在工件识别中的应用[J]. 计算机科学与应用, 2016, 6(8): 485-491.
http://dx.doi.org/10.12677/CSA.2016.68060
参考文献
[
1
]
李阳君. 基于视觉的工件识别定位方法的研究[D]: [硕士学位论文]. 西安: 西安理工大学, 2006.
[
2
]
梁元月. 基于双目立体视觉的工件识别定位方法研究[D]: [硕士学位论文]. 西安: 西安理工大学, 2008.
[
3
]
Luo, Y., Chen, S.W., He, X.J. and Jia, X. (2013) Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features. International Journal of Computational Intelligence Systems, 6, 1108-1115.
http://dx.doi.org/10.1080/18756891.2013.816162
[
4
]
Chen, K., Wang, Y.C., Zhao, P., Banta, L.E. and Zhao, X.M. (2009) Aggregate Image Based Texture Identification Using Gray Level Co-Occurrence Probability and BP Neural Network. Journal of Electronics (China), 26, 428-432.
http://dx.doi.org/10.1007/s11767-008-0153-1
[
5
]
Barbosa, R.M., de Paula, E.S., Paulelli, A.C., Moore, A.F., Souza, J.M.O., Batista, B.L., Campiglia, A.D. and Barbosa, F. (2016) Recognition of Organic Rice Samples Based on Trace Elements and Support Vector Machines. Journal of Food Composition and Analysis, 45, 95-100.
http://dx.doi.org/10.1016/j.jfca.2015.09.010
[
6
]
崔政, 李壮. 两种改进的模板匹配识别算法[J]. 计算机工程与设计, 2006, 27(6): 1083-1085.
[
7
]
陆兴华, 梁建铭, 袁文聪, 郭梓俊. 一种融合角点特征匹配的人脸优化识别方法[J]. 计算机时代, 2016(3): 8-14.
[
8
]
王安静, 陈玲, 宋建永, 金赞. 用VC++实现图像连通区域标记[J]. 电脑编程技巧与维护, 2003(1): 74-77.
[
9
]
杨曼, 贾立峰. 基于模板匹配的水泡识别研究[J]. 机械工程与自动化, 2016(2): 147-151.
[
10
]
高菊, 叶桦. 一种有效的水表数字图像二次识别算法[J]. 东南大学学报, 2013, 43(s1): 153-157.
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