On the connection between the Zernike moments and Radon transform of an image
Pattern Recognition Letters
Recursive computation of Tchebichef moment and its inverse transform
Pattern Recognition
Efficient hardware architectures for computation of image moments
Real-Time Imaging
Image analysis by Tchebichef moments
IEEE Transactions on Image Processing
Efficient computation of local geometric moments
IEEE Transactions on Image Processing
Image analysis by Krawtchouk moments
IEEE Transactions on Image Processing
Some computational aspects of discrete orthonormal moments
IEEE Transactions on Image Processing
High-order moment computation of gray-level images
IEEE Transactions on Image Processing
Real-time computation of Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
Fast Computation of Chebyshev Moments
IEEE Transactions on Circuits and Systems for Video Technology
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Image moments are extensively used in various image analysis tasks. Moments of a discrete orthogonal basis were recently proposed as image descriptors, presenting some advantages over moments of a continuous basis. In this paper, we derive some of their properties regarding geometrical transformations, as well as some computational characteristics. Most of these properties hold for all orthogonal polynomial moments, but when applied to discrete ones, no approximation errors appear. By using these properties, we propose a novel method for the efficient computation of the moments of a 2D object through its projections.