Scale space and affine invariant recognition of occluded shapes
The recently proved existence of affine invariant scale spaces for shapes opens new possibilities for shape recognition. While affine invariant shape recognition is easily performed when shapes are complete, partially occluded or incomplete shapes must be recognized by dividing them into intrinsic parts. The characteristic point method, for instance, focuses on configurations of points with maximal curvature of the shape (in a euclidian invariant framework). Using the affine invariant scale space, we define affine invariant characteristic points and affine invariant parts of a shape. We prove that compatibility scale relations make feasible the matching of scale spaces and show experiments with noisy affine distorted and occluded shapes.
In practical use, objects in still images and videos are easy to misappropriate with handy image-processing tools and need to be pro- tected. However, the few proposals for object watermarking suffer from resynchronization problems. In this study, we develop an object-based watermarking method based on efficient segmentation using lines paral- lel and perpendicular to two principal axes in the spatial domain. A patch- like scheme is designed to embed and extract invisible watermarks. In contrast with the previous object-based watermarking schemes, extra information for resynchronization is not required to be stored in our method. Experimental results show the robustness of the proposed method against many kinds of geometrical attacks. © 2007 Society of Photo-