초록 ▼

The image correlation method and apparatus correlates or matches a test image with a template. The image correlation apparatus includes an image processor for partitioning the template into a number of labels, for determining the total number of pixels N.sub.T which form the template and for determi

The image correlation method and apparatus correlates or matches a test image with a template. The image correlation apparatus includes an image processor for partitioning the template into a number of labels, for determining the total number of pixels N.sub.T which form the template and for determining the number of pixels N.sub.i which form each of the labels i. The image correlation apparatus also includes comparison means for comparing the test image to the template. The comparison means determines, for each predetermined gray level j, the number of pixels of the test image N.sub.j,i representative of a predetermined gray level j which correspond to a predetermined label i of the template. The comparison means also determines, for each predetermined gray level j, the number of pixels of the test image N.sub.j representative of a predetermined gray level j which correspond to the template. The image correlation apparatus further includes correlation means for determining the correlation X between the test image and the template according to a predetermined equation which is based, at least in part, upon N.sub.j,i, N.sub.j, N.sub.i and N.sub.T. The image correlation apparatus can also include an address generator for creating a number of relative offsets between the template and the test image. Thus, the test image can be compared to the template at each relative offset and the relative offset which provides the greatest correlation therebetween can be determined. Consequently, the test image and the template can be effectively matched such that a preselected object designated within the template can be located and identified within the test image.

대표청구항 ▼

[ What is claimed is:] [1.] A method for correlating a test image with a template to identify a specific object wherein both the test image and the template are comprised of a plurality of pixels representative of respective predetermined gray levels, and wherein the template is partitioned into a p

[ What is claimed is:] [1.] A method for correlating a test image with a template to identify a specific object wherein both the test image and the template are comprised of a plurality of pixels representative of respective predetermined gray levels, and wherein the template is partitioned into a plurality of labels comprised of at least one pixel, the method comprising the steps of:dividing the template into a plurality of pieces;comparing each piece of the template to a predetermined region of the test image such that at least some of the pixels of each piece of the template correspond to respective pixels of the test image and such that at least some deformation between the pieces of the template is permitted;separately determining, for each piece of the template and for each of a plurality of predetermined gray levels j, the number of pixels of the test image N.sub.j,i representative of a predetermined gray level j which correspond to a predetermined label i of the respective piece of the template;separately determining, for each piece of the template and for each of a plurality of predetermined gray levels j, the number of pixels of the test image N.sub.j representative of a predetermined gray level j which correspond to the respective piece of the template to identify said object; andseparately determining the correlation X between each piece of the test image and the template according to: ]EQU4 ] wherein N.sub.T is the total number of pixels which comprise the respective piece of the template, N.sub.i is the number of pixels which form each of the plurality of labels i of the respective piece of the template, i.sub.min and i.sub.max are the minimum and maximum label designations, respectively, and j.sub.min and j.sub.max are the minimum and maximum gray levels, respectively.