Method and system for automatically visually inspecting an article

• US 4,928,313 A
• Filed: 05/19/1989
• Issued: 05/22/1990
• Est. Priority Date: 10/25/1985
• Status: Expired due to Term

• Current Assignee: GSI Lumonics Corporation (Novanta Inc.)
• Original Assignee: Synthetic Vision Systems, Inc.
• Inventors: Rohrer, Donald K., Coleman, E. North Jr., Svetkoff, Donald J., Leonard, Patrick F., Kelley, Robert W.
• Primary Examiner(s): Boudreau, Leo H.
• Assistant Examiner(s): Couso, Jose L.
• Application Number:
  US07/355,816
• Time in Patent Office: 368 Days
• Field of Search: 382/8, 382/49, 382/86, 358/101, 358/106, 358/107
• US Class Current: 382/149
• CPC Class Codes: G01N 21/956 Inspecting patterns on the surface of objects contactless testing of electronic circuits G01R31/308; testing currency G07D; manufacturing processes per se of semiconductor devices implementing a measuring step H01L22/10
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/001 using an image reference approach

Abstract

A method and system are disclosed for automatically visually inspecting an article such as an electronic circuit wherein both reference and non-reference algorithms are utilized to detect circuit defects. The system includes a pipelined cellular image processor which is utilized to implement the non-reference algorithm and an arithmetic logic unit (ALU) is coupled to the output of the cellular image processor to perform the reference method. The non-reference method includes a spaces and traces algorithm and the reference method includes a topology matching algorithm. The system also includes an algorithm for locating and gauging critical areas of the circuit with sub-pixel accuracy. The cellular image processor is supported by a matched host image processor system

Claims

1. A method for automatically and visually inspecting an article, the method comprising the steps of:

acquiring a first set of digital image data representing a known good article, the image data representing a two dimensional reference image, processing the first set of image data to separate the reference image into at least two identifiable areas having a boundary therebetween;

compressing the reference image in each of the two dimensions of the reference image, the step of compressing including the steps of reducing at least one of the areas of the reference image to an edge represented by a number of data points and reducing the number of data points representing the edge;

storing the compressed reference image;

acquiring a second set of digital image data representing a two-dimensional image of an article under inspection;

processing the second set of digital image data to separate the image of the article under inspection into at least two identifiable areas having a boundary therebetween;

retrieving the compressed reference image;

regenerating the retrieved reference image, said step of regenerating including the step of regenerating the edge from the reduced number of data points, regenerating the at least one of the areas from the regenerated edge, and constructing border regions around at least one of the areas of the reference image to obtain a regenerated reference image; and

matching the regenerated reference image and the image of the article under inspection to identify areas where mismatches occur.

2. The method as claimed in claim 1 wherein the article includes electronic circuitry such as a multilayer thick-film circuit having a plurality of components.

3. The method as claimed in claim 1 or 2 including the step of measuring at least one dimension of one of the areas of the image of the article under inspection.

4. The method as claimed in claim 1 or 2 further comprising the step of checking the second set of processed data with at least one preselected geometrical constraint to identify areas of non-compliance.

5. The method as claimed in claim 4 wherein the step of checking includes the step of checking the second set of image data with a preselected width constraint.

6. The method as claimed in claim 4 wherein the step of checking includes the step of performing a series of neighborhood transformations on said second set of image data.

7. The method as claimed in claim 6 including the step of generating a bit map flagging the areas of non-compliance.

8. The method as claimed in claim 4 including the step of combining said areas of non-compliance and said areas where the mismatches occur to identify defects.

9. A system for automatically, visually inspecting an article, the system comprising:

means for acquiring first and second sets of digital image data, the first set of image data representing a two-dimensional reference image of a known good article and the second set of image data representing a two-dimensional image of the article under inspection;

means for processing the first set of image data to separate the first set of image data into at least two identifiable areas having a boundary therebetween;

means for compressing the reference image in each of the two dimensions of the reference image, said means for compressing including means for reducing at least one of the areas of the reference image to an edge represented by a number of data points and means for reducing the number of data points representing the edge;

means for storing the compressed reference image;

means for retrieving the stored compressed reference image;

means for regenerating the reference image, said means for regenerating including means for regenerating the edge from the reduced number of data points representing the edge, means for regenerating the at least one of the areas of the reference image from the edge; and

means for constructing border regions from the at least one of the areas of the reference image to obtain the regenerated reference image; and

means for matching the regenerated reference image and the image of the article under inspection to identify areas where mismatches occur.

10. The system as claimed in claim 9 wherein the article includes circuitry such as a multilayer thick film circuit having a plurality of components.

11. The system as claimed in claim 9 wherein said means for matching includes an arithmetic logic unit for comparing the regenerated reference image and the second set of processed image data.

12. The system as claimed in claim 10 further comprising means for checking the set of processed image data with at least one preselected geometrical constraint to identify areas of non-compliance.

13. The system as claimed in claim 12 wherein said means for checking includes a pipeline of serial neighborhood transformation stages for processing the second set of image data.

14. The system as claimed in claim 13 wherein said means for matching includes an arithmetic logic unit selectively coupled to the output of the pipeline and selectively coupled to said means for regenerating for combining the regenerated reference image and the second set of image process data.