Near-optimal mst-based shape description using genetic algorithm

摘要

A new method for the selection of the optimal structuring element for shape description and matching based on the morphological signature transform (MST) is presented in this paper. For a given class of shapes the optimal structuring element for MST method is selected by means of a genetic algorithm. The optimization criteria is formulated to enable a robust shape matching. Experiments have been performed on a class of model shapes. The proposed optimal shape description method is applied to the problem of shape matching which evolves in many object recognition applications. Here, an unknown object is matched to a set of known objects in order to classify it into one of finite number of classes. Experimental results are presented and discussed.