A wavelet approach for partial occluded object recognition

Abstract

A complete 2-D object recognition algorithm applicable for both standalone and partial occluded object is presented. The main contributions in our work are: we developed a scale and partial occlusion invariant boundary partition algorithm and a multiresolution feature extraction algorithm using wavelet. We also implemented a hierarchical matching strategy for feature matching to reduce computational load, but increase matching accuracy. Experiment result shows proposed recognition algorithm is robust to similarity transform and partial occlusion.