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Image moments are weighted sums over pixel values in a given image and areused in object detection and localization. Raw image moments are deriveddirectly from the image and are fundamental in deriving moment invariantsquantities. The current general algorithm for raw image moments iscomputationally expensive and the number of multiplications needed scales withthe number of pixels in the image. For an image of size (N,M), it has O(NM)multiplications. In this paper we outline an algorithm using the Discrete RadonTransformation for computing the raw image moments of a grayscale image. Itreduces two dimensional moment calculations to linear combinations of onedimensional moment calculations. We show that the number of multiplicationsneeded scales as O(N + M), making it faster then the most widely used algorithmof raw image moments.

Using the discrete radon transformation for grayscale image moments