A filter bank method to construct rotationally invariant moments for pattern recognition

We propose multiresolution filter bank techniques to construct rotationally invariant moments. The multiresolution pyramid motivates a simple but efficient feature selection procedure based on a combination of a pruning algorithm, a new version of the Apriori mining techniques and the partially supervised fuzzy C-mean clustering. The recognition accuracy of the proposed techniques has been tested with the reference to conventional methods. The numerical experiments, with more than 50,000 images taken from standard image datasets, demonstrate an accuracy increase ranging from 5% to 27% depending on the noise level.