Image analysis by Bessel-Fourier moments
Image analysis by Bessel-Fourier moments
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DOI：
10.1016/j.patcog.2010.03.013
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发表时间：
2010-08
期刊：
影响因子：
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通讯作者：
Bing Xiao;Jianfeng Ma;Xuan Wang
中科院分区：
文献类型：
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作者：
Bing Xiao;Jianfeng Ma;Xuan Wang
在本文中，我们提出了一个新的矩集的基础上的第一类贝塞尔函数，命名为贝塞尔-傅里叶矩（BFM），这是更适合于图像分析和旋转不变模式识别的正交傅里叶-梅林和Zernike矩。与同阶的正交Fourier-Mellin多项式和Zernike多项式相比，新的正交径向多项式具有更多的零点，并且这些零点分布更均匀。Bessel-Fourier矩可以被认为是广义正交化的复矩。理论和实验结果表明，Bessel-Fourier矩在无噪声、有噪声和平滑失真条件下的图像重建能力和不变识别精度均优于正交Fourier-Mellin矩和Zernike矩（OFWavelet和ZMs）.
In this paper, we proposed a new set of moments based on the Bessel function of the first kind, named Bessel–Fourier moments (BFMs), which are more suitable than orthogonal Fourier–Mellin and Zernike moments for image analysis and rotation invariant pattern recognition. Compared with orthogonal Fourier–Mellin and Zernike polynomials of the same degree, the new orthogonal radial polynomials have more zeros, and these zeros are more evenly distributed. The Bessel–Fourier moments can be thought of as generalized orthogonalized complex moments. Theoretical and experimental results show that the Bessel–Fourier moments perform better than the orthogonal Fourier–Mellin and Zernike moments (OFMMs and ZMs) in terms of image reconstruction capability and invariant recognition accuracy in noise-free, noisy and smooth distortion conditions.