Statistical moments have been used in different applications as in shape analysis of object, pattern recognition, edge detection texture analysis etc. The idea is to use the moments as features of high level for surface matching. The essential goal of surface matching is to determine transformation parameters between two surfaces generated in TIN or DEM without identical points. Statistical moments are considered as features that are applied to solve that goal, One of the main problems with using statistical moments for surface matching and for other applications is a very expensive computation time. To overcome this difficulty many algorithms have already been proposed. New approach of efficient computation of inertial moments for surface matching is proposed in the paper. The approach is based on Green's theorem that allows for transforming double integral into a line integral. In the consequence computation time of inertial moments of a single TIN-model (triangle) is reduced by a factor 4 as compared with time consumed by the use of direct method of double integral. The direct computation using line integral, that does not involve any approximation, ensures preservation of the accuracy of computed moments.

The purpose of surface matching is to determine transformation parameters without known corresponding points for two data sets of spatial point coordinates obtained with use of different sensors. Instead of different features such as points of interest, lines, surface patches in the TIN (Triangle Irregular Network) or DEM model are used. The paper presents an approach of using inertial moments of TIN models generated from two data sets of same terrain for surface matching. The inertial moments could easily be calculated for each triangle in the TIN using formulae given. Three moment invariants/,./,,,,"/""'' that are used as the features of high level for surface matching are defined.

The paper presents the line moments of edge contour detected in an image as the high level features which are useful for surface matching. It has been proved that line moments do not depend on scale and rotation in transformation and they are sensitive to small changes of line erroneously extracted. Therefore, line moments are the useful tools in the process of feature-based matching, which can be used for merging (comparing) two surfaces derived with different sensors for the same terrain scene. In order to receive a line in an image, the edge pixels of terrain contour have to be detected and then linked into a line. The paper also focuses on the problem of using wavelet transform for automatic detection of edge pixels. The suggestion of 3-D line moments for surface matching has been presented in the section 5.