2013
DOI: 10.1007/s10851-013-0456-1
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Error Analysis in the Computation of Orthogonal Rotation Invariant Moments

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Cited by 43 publications
(11 citation statements)
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“…The Zernike polynomials are orthogonal. Therefore it can draw out the Zernike moments from a ROI irrespective of the shape of the target [4]. The formulation of Zernike moment appears to be very favored, outperforming the options (in phrase of noise resilience, information redundancy and reconstruction capability).…”
Section: A Orthogonal Rotation Invariant Moment (Orim)mentioning
confidence: 99%
See 1 more Smart Citation
“…The Zernike polynomials are orthogonal. Therefore it can draw out the Zernike moments from a ROI irrespective of the shape of the target [4]. The formulation of Zernike moment appears to be very favored, outperforming the options (in phrase of noise resilience, information redundancy and reconstruction capability).…”
Section: A Orthogonal Rotation Invariant Moment (Orim)mentioning
confidence: 99%
“…Sergio Dominguez [3] proposed a technique for the recognition of 3-D object and pose analysis. Chandan et al [4] proposed a technique for the error computation, Sheng et al proposed OFMMs [5], [8] for pattern recognition. The amounts of OMs are invariant to the variation of the signal [6].…”
Section: Introductionmentioning
confidence: 99%
“…图 2 显示了极谐 -Fourier 矩的径向基函数 A n (r), 可以看出, 当 r → 0 时, A n (r) ∈ [0, 1], 这说 明使用高阶矩重构图像时, 图像中心区域的重构效果不会变差 [18] . 图 3 为使用极谐 -Fourier 矩和 圆谐 -Fourier 矩对大小为 128 × 128 的 Lena 图像及其二值图像的重构对比图 (最大矩阶数 n max = 5,10,15,20,25,30).…”
Section: 基于上述问题 本文使用 R 2 代替 R 定义如下径向基函数unclassified
“…For further details one can refer Refs. [20,24]. Despite these errors, the magnitude of RIMTs provides satisfactory results for many practical applications.…”
Section: Similarity Weight Computation Using Rimt-unlmmentioning
confidence: 99%
“…The difference in CPU elapse time is more apparent for large images. Although in our experiments we adopt the fast computation of ZMs [22][23][24][25], ART has speed advantage over ZMs due to its low computation complexity, thus providing minimum CPU elapse time for all images. The proposed ZM-UNLM-based approach with order of moment p max = 4 uses only nine moments which are sufficient to represent the useful characteristics of an image, whereas the existing DCT-UNLM approach uses 15 DCT coefficients extracted in a zig-zag manner.…”
Section: Speed Analysismentioning
confidence: 99%