Curve Representing and Matching Based on Feature Points and Minimal Area Threshold

A new method for representing and recognizing the contour curve is presented in this paper. First, feature points are employed to describe contour curve preliminarily; Then the sample points of the sub-curve are introduced to describe contour more, they are obtained based on the precision requirement using the given minimal area threshold. A new recognition vector of sample points is defined, and a novel recognition vector matrix is constructed based on the recognition vector of sample points; Last the dissimilarity measure of the corresponding sub-curves is calculated by compared the recognition vector matrix. The curves are recognized by recognizing their each sub-curve. The method match object and model from simple to complex, thus many redundancies calculation are avoided The experiment results show the algorithm is efficient and feasible.