Mapping vector accumulator: fractal domain feature for character recognition

A new feature is presented which is calculated directly from the fractal-compressed form of images. The performance of this feature is analysed by using it in the training of standard classifiers for a character recognition problem. The feature is shown to be translation invariant, giving it an advantage over methods that use pixels or compressed data directly.