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Geometric moments and moment invariants of image artifacts have many uses incomputer vision applications, e.g. shape classification or object position andorientation. Higher order moments are of interest to provide additional featuredescriptors, to measure kurtosis or to resolve n-fold symmetry. This paperprovides the method and practical application to extend an efficient algorithm,based on the Discrete Radon Transform, to generate moments greater than the 3rdorder. The mathematical fundamentals are presented, followed by relevantimplementation details. Results of scaling the algorithm based on image areaand its computational comparison with a standard method demonstrate theefficacy of the approach.

Efficient Computation of Higher Order 2D Image Moments using the Discrete Radon Transform