Corresponding Points Matching Based on Position Similarity

According to the position similarity of corresponding points in correlative images, a rule of points matching based on “the regulation of the minimum summation of Euclid distance” is presented when studying the problem of corresponding points matching from X-ray images. This rule is different from the conventional corresponding points matching methods based on gray level or region geometric feature. It derives from the model of sequence matching algorithm. According to the condition that the relative position of any two points in adjacent area from two images are almost unchanged, this rule minimizes the summation of corresponding points distance by adjusting the sequence of points with evolutionary programming searching algorithm to match corresponding points. From the experiment on PC, the result demonstrates that this approach can match the most feature points correctly in a low cost of time just based on the position of corresponding points.