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Image analysis by fast improved radial harmonic-Fourier moments algorithm

机译:快速改进径向谐波矩阵算法的图像分析

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摘要

Radial harmonic-Fourier moments (RHFMs) are popular for image reconstruction and invariant pattern recognition due to their properties of translation, scaling and rotation invariant. RHFMs possess lower computation complexity as compared to Zernike moments and Bessel-Fourier moments. However, they always suffer from discontinuity, numerical instability near the center of image, and reconstruction error, especially have a rise for higher order of moments. In this paper, an improvement of radial harmonic-Fourier moments (IRHFMs) is proposed for effectively avoiding the above-mentioned problems.In this paper, a 2D fast Fourier transform algorithm also is applied to the image matrix to obtain the IRHFMs. Simulation experimental results demonstrate the proposed IRHFMs perform better than traditional RHFMs and other classic orthogonal moments including the latest image moments, for example, polar harmonic Fourier moments in terms of the image reconstruction capability and rotation invariant recognition accuracy in noise-free and noisy conditions.
机译:由于它们的翻译,缩放和旋转不变的属性,径向谐波 - 傅立叶矩(RHFMS)是图像重建和不变模式识别的流行。与Zernike的时刻和贝塞尔傅立叶矩相比,RHFMS具有较低的计算复杂性。然而,它们总是在图像中心附近遭受不连续性,数值不稳定性,并且重建误差,特别是升级的时刻上升。在本文中,提出了提高径向谐波 - 傅立叶矩(IRHFMS)的改进,以有效地避免上述问题。在本文中,2D快速傅里叶变换算法也应用于图像矩阵以获得IRHFMS。仿真实验结果展示了所提出的IRHFMS比传统的RHFMS和其他经典正交时刻更好地表现出包括最新图像时刻的其他经典正交时刻,例如,在图像重建能力和旋转不变的识别精度方面,偏光和嘈杂的条件方面的偏振谐波瞬间。

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