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

机译:正交傅里叶-梅林矩快速计算的高效算法

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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:与传统的Zemike矩相比,正交Fourier-Mellin矩具有更好的特征提取功能,并且对图像噪声更健壮。然而,由于正交傅里叶-梅林径向多项式的计算复杂性,正交傅里叶-梅林矩并未被广泛用作模式识别的特征。本文分析了现有方法的不足,并介绍了一种有效的递归算法来计算正交傅里叶-梅林矩。该算法由Mellin正交径向多项式的递归关系组成,该关系式是从Jacobi多项式导出的,用于快速计算正交Fourier-Mellin矩。设计了一个使用二进制图像的实验来测试算法的性能。实验结果表明,与现有方法相比,正交傅里叶-梅林矩的计算速度得到了充分的提高。

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