Improvement of image matching algorithm based on gray correlation

Gray correlation based minimum error and correlation coefficient algorithms were improved to eliminate the disadvantages of low matching accuracy and slow matching velocity existing in the image matching algorithms nowadays．In the improved minimum error algorithm, a new ML distance method is adopted and a threshold dynamic adjustment method is proposed to assure the matching accuracy and to avoid the influence of local noises. As for the correlation coefficient algorithm, the expression of correlation coefficient is simplified and three-step searching way is used to reduce the compexity of the calculation and to achieve the goal of the position acquisition. The experiment shows that the improved algorithms greatly increase the matching velocity without the loss of matching accuracy，and meet the requirement of real-time image matching system.