On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthogonal Moment Features for Use With Parametric and Non-Parametric Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Digital Signal Processing and Modeling
Statistical Digital Signal Processing and Modeling
Content-based trademark retrieval system using visually salient features
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image analysis by moments
New computational methods for full and subset Zernike moments
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
EURASIP Journal on Applied Signal Processing
On the reconstruction aspects of moment descriptors
IEEE Transactions on Information Theory
Fast computation of geometric moments using a symmetric kernel
Pattern Recognition
Fast and accurate method for radial moment's computation
Pattern Recognition Letters
Fast and numerically stable methods for the computation of Zernike moments
Pattern Recognition
Image quality assessment by discrete orthogonal moments
Pattern Recognition
Algorithms for fast computation of Zernike moments and their numerical stability
Image and Vision Computing
Fast computation of exact Zernike moments using cascaded digital filters
Information Sciences: an International Journal
Analysis of algorithms for fast computation of pseudo Zernike moments and their numerical stability
Digital Signal Processing
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The applications of radial moment functions such as orthogonal Zernike and pseudo-Zernike moments in real-world have been limited by the computational complexity of their radial polynomials. The common approaches used in reducing the computational complexity include the application of recurrence relations between successive radial polynomials and coefficients. In this paper, a novel approach is proposed to further reduce the computation complexity of Zernike and pseudo-Zernike polynomials based on the symmetrical property of radial polynomials. By using this symmetrical property, the real-valued radial polynomials computation is reduced to about one-eighth of the full set polynomials while the computation of the exponential angle values is reduced by half. This technique can be integrated with existing fast computation methods to further improve the computation speed. Besides significant reduction in computation complexity, it also provides vast reduction in memory storage.