[1]江克,陈北京,张辉,等.完备的Zernike矩不变量集的构造及应用[J].东南大学学报(自然科学版),2011,41(1):58-62.[doi:10.3969/j.issn.1001-0505.2011.01.012]
 Jiang Ke,Chen Beijing,Zhang Hui,et al.Construction of complete set of Zernike moment invariants and its application[J].Journal of Southeast University (Natural Science Edition),2011,41(1):58-62.[doi:10.3969/j.issn.1001-0505.2011.01.012]
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完备的Zernike矩不变量集的构造及应用()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
41
期数:
2011年第1期
页码:
58-62
栏目:
计算机科学与工程
出版日期:
2011-01-20

文章信息/Info

Title:
Construction of complete set of Zernike moment invariants and its application
作者:
江克12陈北京23张辉2舒华忠2
(1东南大学生物科学与医学工程学院,南京210096)
(2东南大学影像科学与技术实验室,南京210096)
(3宁波工程学院电子与信息工程学院,宁波315016)
Author(s):
Jiang Ke12Chen Beijing23Zhang Hui2Shu Huazhong2
(1School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China)
(2Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China)
(3School of Electronic
关键词:
Zernike矩不变量完备性图像分类
Keywords:
Zernike moment invariant completeness image classification
分类号:
TP391
DOI:
10.3969/j.issn.1001-0505.2011.01.012
摘要:
为了解决模式识别应用中传统的不变量特征之间的相关性问题,基于Zernike矩提出一种构造其完备的相似变换不变量集的新方法.首先,根据图像的Zernike矩与径向矩之间的关系,以径向矩为中间桥梁,建立原图像的Zernike矩和旋转缩放后图像的Zernike矩之间的关系,然后由原图像的同阶和低阶Zernike矩线性组合即可得到完备的Zernike矩旋转和缩放不变量集.类似地,可以构造完备的Zernike矩平移不变量.并将两者结合最终得到Zernike矩的相似变换不变量完备集.图像分类实验结果表明,与现有的一些方法相比,所提出的方法在分类正确率和运算时间方面的效果更好,具有较强的噪声鲁棒性.
Abstract:
To resolve the dependence problem of traditional invariant features in pattern recognition, a new method to derive a complete set of Zernike moments similarity invariants is presented. Firstly, based on the connection between Zernike moments and radial moments, the relationship between Zernike moments of the original image and those of the images having the same shape but distinct scale and orientation is established. Then through a linear combination of original Zernike moments with same and lower order a complete set of scale and rotation invariants can be formed. By the same method, a complete set of translation invariants can be derived. Finally, the complete set of Zernike moment similarity invariants (rotation, scale and translation, RST) can be obtained. Experimental results demonstrate that the proposed method performs better than the existing methods in both classification accuracy rate and computational time.

参考文献/References:

[1] Hu M K.Visual pattern recognition by moment invariants [J].IRE Transaction on Information Theory,1962,IT-8(2):179-187.
[2] Teh C H,Chin R T.On image analysis by the method of moments [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1988,10(4):496-513.
[3] Belkasim S,Shridhar M,Ahmadi M.Pattern recognition with moment invariants:a comparative study and new results [J].Pattern Recognition,1991,24(12):1117-1138.
[4] Kan C,Srinath M D.Invariant character recognition with Zernike and orthogonal Fourier-Mellin moments [J].Pattern Recognition,2002,35(1):143-154.
[5] Belkasim S,Hassan E,Obeidi T.Explicit invariance of Cartesian Zernike moments [J].Pattern Recognition Letters,2007,28(15):1969-1980.
[6] Chong C W,Raveendran P,Mukundan R.Translation invariants of Zernike moments [J].Pattern Recognition,2003,36(8):1765-1773.
[7] Jan F.On the independence of rotation moment invariants[J].Pattern Recognition,2000,33(9):1405-1410.
[8] Wallin A,Kubler O.Complete sets of complex Zernike moment invariants and the role of pseudoinvariants [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1995,17(11):1106-1110.
[9] Shu H Z,Luo L M,Han G N,et al.A general method to derive the relationship between two sets of Zernike coefficients corresponding to different aperture sizes [J].Journal of the Optical Society of America A,2006,23(8):1960-1966.
[10] Mukundan R,RamaKrishnan K R.Moment Functions in image analysis-theory and applications [M].Singapore:World Scientific Press,1998:12-13.
[11] Nene S A,Nayar S K,Murase H.Columbia University Image Library (COIL-20) [EB/OL].(1996-02)[2010-05-23].http://www1.cs.columbia.edu/CAVE/software/softlib/coil-20.php.
[12] Chong C W,Raveendran P,Mukundan R.The scale invariants of pseudo-Zernike moments [J].Pattern Analysis and Applications,2003,6(3):176-184.

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备注/Memo

备注/Memo:
作者简介:江克(1985—),女,硕士生;舒华忠(联系人),男,博士,教授,博士生导师,shu.list@seu.edu.cn.
基金项目:国家自然科学基金资助项目(61073138)、江苏省自然科学基金资助项目(BK2008279,BK2009012)、宁波市自然科学基金资助项目(2010A610106).
引文格式: 江克,陈北京,张辉,等.完备的Zernike矩不变量集的构造及应用[J].东南大学学报:自然科学版,2011,41(1):58-62.[doi:10.3969/j.issn.1001-0505.2011.01.012]
更新日期/Last Update: 2011-01-20