A PCA-Based Method for Image Matching of Workpiece
NI Hong-qi · Journal of Northeastern University · 2008
To speed up the computation for workpiece image matching,a novel PCA(principal component analysis) method is proposed taking the template image as a multi-dimension set of spatial points,to which the PCA is made.Then,the number of principal components is determined to ensure the information reserving rate,thus obtaining the maximum and minimum projection values(MM-vectors) in all directions of those components as well as the serial numbers of rows in corresponding template images.While matching,only the principal component directions corresponding to the rows of the same serial numbers in searching area are needed to be extracted for the computation of projection value so as to form the vectors of projection values.The distances between MM-vectors and the vectors formed by projection values are computed,and whether the two kinds of vectors are matchable should be in accordance to those distances.During the matching an improved genetic algorithm is used for optimization.The matching results of workpiece images show the high optimizing speed and precision of the proposed method,even if the images to be matched are mixed with high decibel noise.