Image processing method and apparatus for correlating a test image with a template

• US 5,890,808 A
• Filed: 01/13/1998
• Issued: 04/06/1999
• Est. Priority Date: 01/05/1996
• Status: Expired due to Term

• Current Assignee: Mcdonnell Douglas Corporation (The Boeing Co.)
• Original Assignee: Mcdonnell Douglas Corporation (The Boeing Co.)
• Inventors: Wright, Steven A., Neff, Michael G., Johnson, Ted L., Ratkowski, Victor E. Jr.
• Primary Examiner(s): Shalwala, Bipin
• Assistant Examiner(s): Mariam, Daniel G.
• Application Number:
  US09/006,407
• Time in Patent Office: 448 Days
• Field of Search: 382/181, 382/124, 382/126, 382/209, 382/219, 382/278, 382/218, 356/71
• US Class Current: 382/209
• CPC Class Codes: F41G 7/007 Preparatory measures taken before the launching of the guided missiles
• CPC Class Codes: F41G 7/2226 comparing the observed data with stored target data, e.g. target configuration data
• CPC Class Codes: F41G 7/2253 Passive homing systems, i.e. comprising a receiver and do not requiring an active illumination of the target
• CPC Class Codes: F41G 7/2293 using electromagnetic waves other than radio waves
• CPC Class Codes: G06T 7/337 involving reference images or patches
• CPC Class Codes: G06V 10/751 Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
• CPC Class Codes: G06V 10/7515 Shifting the patterns to accommodate for positional errors
• CPC Class Codes: G06V 10/94 Hardware or software architectures specially adapted for image or video understanding

Abstract

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_T which form the template and for determining the number of pixels N_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_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_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_j,i, N_j, N_i and N_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.

Claims

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_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_j representative of a predetermined gray level j which correspond to the respective piece of the template to identify said object; and

separately determining the correlation X between each piece of the test image and the template according to;

##EQU4## wherein N_T is the total number of pixels which comprise the respective piece of the template, N_i is the number of pixels which form each of the plurality of labels i of the respective piece of the template, i_min and i_max are the minimum and maximum label designations, respectively, and j_min and j_max are the minimum and maximum gray levels, respectively.

2. A method according to claim 1 further comprising the step of determining an overall correlation between the test image and the template, said overall correlation determining step comprising the step of summing the respective correlation determined for each piece of the template.

3. A method according to claim 1 further comprising the step of creating a plurality of relative offsets between the pieces of the template and the test image, wherein said comparing step comprises the step of comparing the pieces of the template to the test image at each relative offset, wherein said N_j,i determining step comprises the step of determining, for each piece of the template and at each relative offset, the number of pixels of the test image N_j,i representative of a predetermined gray level j which correspond to a predetermined label i of the respective piece of the template, wherein said N_j determining step comprises the step of determining, for each piece of the template and at each relative offset, the number of pixels of the test image N_j representative of a predetermined gray level j which correspond to the respective piece of the template, and wherein said correlation determining step comprises the step of determining the correlation X between the test image and each piece of the template at each relative offset.

4. A method according to claim 3 further comprising the step of separately determining the relative offset between the test image and each piece of the template which provides the greatest correlation therebetween.

5. A method according to claim 4 further comprising the step of determining an overall correlation between the test image and the template, said overall correlation determining step comprising the step of summing the respective greatest correlation determined for each piece of the template.

6. A method according to claim 3 wherein said relative offset creating step comprises creating respective relative offsets for each piece of the template which permit adjacent pieces of the template to partially overlap.

7. A method according to claim 3 wherein said relative offset creating step comprises creating respective relative offsets for each piece of the template which permit adjacent pieces of the template to be spaced apart by a predetermined gap.

8. An apparatus for correlating a test image and 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 apparatus comprising:

an image processor for dividing the template into a plurality of pieces;

comparison means, responsive to said image processor, for comparing each piece of the template to a predetermined range 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, wherein said comparison means comprises;

means for 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_j,i representative of a predetermined gray level j which correspond to a predetermined label of the respective piece of the template;

means for 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_j representative of a predetermined gray level j which correspond to the respective piece of the template; and

correlation means, responsive to said template processing means and said comparison means, for separately determining the correlation X between the test image and each piece of the template to identify said object according to;

##EQU5## wherein N_T is the total number of pixels which comprise the respective piece of the template, N_i is the number of pixels which form each of the plurality of labels i of the respective piece of the template, i_min and i_max are the minimum and maximum label designations, respectively, and wherein j_min and j_max are the minimum and maximum gray levels, respectively.

9. An apparatus according to claim 8 further comprising the means, responsive to said correlation means, for determining an overall correlation between the test image and the template, said overall correlation determining means comprising means for summing the respective correlation determined for each piece of the template.

10. An apparatus according to claim 8 further comprising offset means for creating a plurality of relative offsets between the pieces of the template and the test image, wherein said comparison means is responsive to said offset means for comparing the pieces of the template to the test image at each relative offset, wherein said N_j,i determining means comprises means for determining, for each piece of the template and at each relative offset, the number of pixels of the test image N_j,i representative of a predetermined gray level j which correspond to a predetermined label i of the respective piece of the template, wherein said N_j determining means comprises means for determining, for each piece of the template and at each relative offset, the number of pixels of the test image N_j representative of a predetermined gray level j which correspond to the respective piece of the template, and wherein said correlation means comprises means for determining the correlation X between the test image and each piece of the template at each relative offset.

11. An apparatus according to claim 10 further comprising means, responsive to said correlation means, for separately determining the relative offset between the test image and each piece of the template which provides the greatest correlation therebetween.

12. An apparatus according to claim 11 further comprising the means, responsive to said greatest correlation determining means, for determining an overall correlation between the test image and the template, said overall correlation determining means comprising means for summing the respective greatest correlation determined for each piece of the template.

13. An apparatus according to claim 10 wherein said offset means creates respective relative offsets for each piece of the template which permit adjacent pieces of the template to partially overlap.

14. An apparatus according to claim 10 wherein said offset means creates respective relative offsets for each piece of the template which permit adjacent pieces of the template to be spaced apart by a predetermined gap.