A Fourier Descriptor based on Zernike Invariant Moments in Spherical Coordinates for 3D Pollen Image Recognition

被引：0
|
作者：
Xie Yonghua [1 ]
Xu Zhaofei [2 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Engn Ctr Network Monitoring, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing, Jiangsu, Peoples R China
来源：
2015 8TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI) | 2015年
关键词：
3D spherical; Zernike moments; genetic algorithm; Fourier; support vector machine (SVM); SYMBOL RECOGNITION;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
This paper presents a new feature extraction method of Fourier descriptor based on the Zernike moments for pollen images recognition. Firstly, Zernike moments of the image are extracted in 3D spherical coordinates. Secondly, genetic algorithm based on probability is used to filter the Zernike moments to reduce redundant information. Finally the normalized Fourier transform coefficients are calculated as the last feature descriptor. The simulation results on Confocal dataset show that the descriptor can effectively describe the pollen images and is robust to the rotation, translation and scaling of the image.
引用
收藏
页码：453 / 457
页数：5
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