Interest points from the radial mass transform [image representation applications]

The radial mass transform (RMT) is defined to produce a rotation and translation invariant vector representation of the neighborhood structure of points. The RMT transforms 3D (or 2D) data sets into a 1D signal where m(p, r) gives the total mass (or intensity) of sensed data at distance r from the point p. A support vector machine can be trained on example signals to detect salient points in an entire image or volume. Results show the method to be effective in multiple applications. The method is computation intensive but highly parallelizable and feasible for high value data sets.