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Inertia Axes are involved in many techniques for image content measurementwhen involving information obtained from lines, angles, centroids... etc. Weinvestigate, here, the estimation of the main axis of inertia of an object inthe image. We identify the coincidence conditions of the Scale Space RadonTransform (SSRT) maximum and the inertia main axis. We show, that by choosingthe appropriate scale parameter, it is possible to match the SSRT maximum andthe main axis of inertia location and orientation of the embedded object in theimage. Furthermore, an example of use case is presented where binary objectscentral symmetry computation is derived by means of SSRT projections and theaxis of inertia orientation. To this end, some SSRT characteristics have beenhighlighted and exploited. The experimentations show the SSRT-based main axisof inertia computation effectiveness. Concerning the central symmetry, resultsare very satisfying as experimentations carried out on randomly created imagesdataset and existing datasets have permitted to divide successfully theseimages bases into centrally symmetric and non-centrally symmetric objects.

Scale space radon transform-based inertia axis and object central symmetry estimation