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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (10): 1749-1756    DOI: 10.3785/j.issn.1008-973X.2009.10.001
机械工程     
图像散布图和小波多分辨分析的模具异物检测
毛锋,张树有,黄长林
(浙江大学 CAD & CG国家重点实验室,浙江 杭州 310027)
Inspection of foreign substances in mould using image scattergrams and multi|resolution analysis
MAO Feng, ZHANG Shu-you, HUANG Chang-lin
(State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou 310027,China)
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摘要：

为了实现成型生产时模具的自动保护,提出基于散布图模具异物检测方法.采集模具监控图像,建立以灰度为变量的散布图,分析两幅图像对应像素灰度的概率分布及回归关系,实现了检测的光照无关性.基于B样条进行回归线构造,采用散点离差统计直方图获得图像间的匹配置信区间,从而得出异物对应的失配像素集.采用小波多分辨分析的方法,通过对两幅图像分别进行同阶小波分解,获得了消除边缘细节的逼近图像,使得后续的异物检测排除了对比图像之间错位的影响,解决了检测中的图像几何偏差问题.通过应用验证了该方法的良好效果.
Abstract:

A method for detecting foreign substances in mould based on scattergrams was presented to protect moulds automatically during moulding production. In order to make the algorithm illumination invariant, a gray level scattergram was plotted, and the regression relation between the pair of compared images was derived by analyzing the probability distribution of the corresponding pixel gray in the two images. The regression curve was constructed using B-spline, and the width of confidence interval was obtained by deviation statistical histogram to detect the false matching pixels representing the foreign substance. Multi-resolution analysis(MRA) was used before inspection in order to solve the problem of the geometric deviation between two images. Wavelet decomposition of the two images was conducted to give an approximate image, which eliminated the edge details from the original images. The method was verified by several images．
出版日期: 2009-11-29
:  TP391.41  
基金资助:

 国家科技支撑计划资助项目(2007BAF13B02);浙江省自然科学基金资助项目(Z1080339、Y107431).
通讯作者: 张树有，男，教授，博导.     E-mail: zsy@zju.edu.cn
作者简介: 毛锋（1984-），男，浙江龙游人，硕士生，主要研究方向为CAD、图像处理、机器视觉等.
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引用本文:

毛锋, 张树有, 黄长林. 图像散布图和小波多分辨分析的模具异物检测[J]. J4, 2009, 43(10): 1749-1756.

MAO Feng, ZHANG Shu-Wei, HUANG Chang-Lin. Inspection of foreign substances in mould using image scattergrams and multi|resolution analysis. J4, 2009, 43(10): 1749-1756.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.10.001    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I10/1749

［1］ 孙吉花,刘肖琳.光照变化的背景减除新算法［J］.计算机仿真,2007,24(9):214217．
SUN Ji-hua, LIU Xiao-lin. A new background subtraction algorithm for varing illumination［J］.Computer Simulation,2007,24(9):214217．
［2］ WU Quen-zong, JENG B S. Background subtraction based on logarithmic intensities［J］. Pattern Recognition Letters, 2002, 23(13): 15291536．
［3］BROMILEY P A,THACKER N A,COURTNEY P. Non- parametric image subtraction using grey level scattergrams ［J］.Image and Vision Computing,2002,20(9/10):609 617．
［4］ 明英,蒋晶珏. 视觉监视中基于柯西分布的统计变化检测［J］.中国图象图形学报,2008,13(2):328334．
MING Ying, JIANG Jing-jue. Cauchy distribution based on statistical change detection for visual surveillance［J］. Journal of Image and Graphics, 2008,13(2):328334．
［5］ 章毓晋.图象处理和分析［M］.北京:清华大学出版社,1999: 118121．
［6］ AWRANGJEB M,MURSHED M,LU Guo-jun; Global geometric distortion correction in images［C］//2006 IEEE 8th Workshop on Multimedia Signal Processing. Piscataway: Institute of Electrical and Electronics Engineers Computer Society, 2007:435440．
［7］ KIM Y H,MARTINEZ A M, KAK A C. Robust motion estimation under varying illumination［J］. Image and Vision Computing,2005,23(4):365375．
［8］ DAUBECHIES I.小波十讲(Ten Lectures on Wavelets)［M］.李建平,杨万年，译.北京：国防工业出版社,2004:127153．
［9］ 程正兴,林勇平.小波分析在图像处理中的应用［J］.工程数学学报,2001,18(5):5786．
CHENG Zheng-xing, LIN Yong-ping. Some applications in image procession with wavelets［J］.Journal of Engineering Mathematics, 2001,18(5)．
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