Moment functions have been defined in [1] and important properties such as invariance and robustness to noise have been reviewed in the second paper [2]. Before addressing applications of moments, another feature has to be discussed, the computational load. The complexity of image analysis methods, in other words the number of operations they require to achieve a given task, iteratively or not, may lead to practical limitations when dealing with large data sets (2D or 3D image sequences) and time constraints. This issue is also of concern for moments in particular when high orders have to be computed. Special attention must therefore be paid to fast computation. The continuous-to-discrete transform may also affect the analytical properties we must preserve (i.e. invariance, orthogonality, etc.) by introducing numerical errors. The problem of accurate computation of moments should thus be addressed. These two aspects are examined in this third paper.