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An Efficient Algorithm for Fast Computation of Orthogonal Fourier-Mellin Moments

机译:一种高效的正交傅立叶蛋白矩的计算算法

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Orthogonal Fourier-Mellin moments have better feature extraction capabilities and are more robust to image noise than the classical Zemike moments. However, orthogonal Fourier-Mellin moments have not been widely used as features in pattern recognition due to the computational complexity of the orthogonal Fourier-Mellin radial polynomials. This paper analyzes the deficiencies of the existing methods, and introduces an efficient recursive algorithm to compute the orthogonal Fourier-Mellin moments. The algorithm consists of a recurrence relation for Mellin orthogonal radial polynomials, which derived from the Jacobi polynomials for fast computation of orthogonal Fourier-Mellin moments. An experiment using binary image is designed to test the performance of the algorithm. The experimental result demonstrates that the computational speed of orthogonal Fourier-Mellin moments has been adequately improved over the present methods.
机译:正交的傅立叶蛋白矩具有更好的特征提取能力,并且比古典Zemike时刻更强大到图像噪声。然而,由于正交傅里叶型径向多项式的计算复杂性,正交的傅里叶蛋白矩未被广泛用作模式识别中的特征。本文分析了现有方法的缺陷,并引入了一种有效的递归算法来计算正交的傅里叶蛋白矩。该算法包括用于MELLIN正交径向多项式的复发关系,其衍生自Jacobi多项式以用于快速计算正交傅里叶蛋白矩。使用二进制图像的实验旨在测试算法的性能。实验结果表明,通过本方法充分改善了正交傅里叶蛋白矩的计算速度。

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