Rotation and Scale Invariant Shape Representation and Recognition Using Matching Pursuit

Using a low-level representation of images, like matching pursuit, we introduce a new way of describing objects through a general description using a translation, rotation, and isotropic scale invariant dictionary of basis functions. This description is then used as a predefined dictionary of the object to conduct a shape recognition task. We show some promising results for both parts of description and detection with simple shapes.