Ophthalmic lens inspection method and apparatus

• US 5,717,781 A
• Filed: 02/07/1996
• Issued: 02/10/1998
• Est. Priority Date: 12/21/1992
• Status: Expired due to Term

• Current Assignee: Johnson & Johnson Vision Products, Inc.
• Original Assignee: Johnson & Johnson Vision Products, Inc.
• Inventors: Sites, Peter, Ebel, James A.
• Primary Examiner(s): Boudreau, Leo
• Assistant Examiner(s): KELLEY, CHRISTOPHER S
• Application Number:
  US08/598,068
• Time in Patent Office: 734 Days
• Field of Search: 382/141, 382/142, 382/143, 348/86, 348/127, 348/131, 356/124, 364/473
• US Class Current: 382/141
• CPC Class Codes: G01M 11/025 by determining the shape of the object to be tested measuring contours or curvatures by optical means G01B11/24
• CPC Class Codes: G01M 11/0278 Detecting defects of the object to be tested, e.g. scratches or dust investigating the presence of flaws or contamination on materials by optical means G01N21/88

Abstract

Disclosed is an ophthalmic lens inspection method and apparatus comprising a camera to capture an image of an ophthalmic lens which has been illuminated by a light source. Location and intensity at each camera pixel is converted to an electrical quantity which is then transferred and stored in a memory. A computer containing instructions for comparing the intensity and location values of the pixels starts near the center of the receptor field and continues toward the edge of the field until an intensity deviation is encountered. By evaluating the pixels containing intensity variation, an outline of the lens edge is attained. An annulus is generated enclosing the actual lens edge. All the pixels are changed from an absolute intensity value to a gradient value, represented by two transition edges. Feature extraction is performed to locate defective pixels and place them into groups. Once the groups have been determined each is given a score based on the number, type and severity of the defective pixels placed into that group. From that, a weighted score can be given to the entire lens and the lens either passes or fails.

Claims

1. A method for inspecting an ophthalmic lens comprising:

capturing an image of the lens for at least one electro-magnetic frequency, the image divided into a group of pixels, each pixel representing a portion of the lens;

converting the intensity value of the pixels into related electrical signals;

assigning a position value and an image intensity value;

comparing position values and image intensity values among pixels to establish a pixel relationship;

identifying from the pixel relationship, sets of pixels corresponding to at least three of the following features of the lens;

radial deviation and spatial derivative of the position values localized gradient deviation, dip localized gradient deviation, and one-tail localized gradient deviation of the intensity values, and discontinuity; and

comparing the features identified from the pixel relationship in said set to a preestablished relationship to ascertain if a lens is acceptable.

2. The method of claim 1 wherein the comparison between pixels is performed along a path following the contour of the lens edge.

3. The method of claim 1 wherein the identification of features comprises collecting pixels sharing a feature characteristic to form a set of pixels.

4. The method of claim 1 wherein the comparison is among a set of pixels comprising the lens edge.

5. The method of claim 1 wherein the comparison is among a set of pixels comprising a portion of the lens interior.

6. The method of claim 2 wherein the lens edge is first located by starting at a point proximate the center of the group of pixels and proceeding toward the boundary of the group of pixels until a pixel having an intensity value characteristic of a lens edge is located.

7. The method of claim 6 wherein additional pixels proximate the pixel having an intensity value characteristic of a lens edge the contour of a set of connected pixels having an intensity value characteristic of a lens edge is followed to determine if the contour is that of a lens edge.

8. The method of claim 4 wherein a processing annulus is set about the lens edge to limit the number of pixels processed to those proximate the lens edge.

9. The method of claim 4 wherein the set of pixels comprising the lens edge is further divided into two subsets of pixels for performing said comparison, a subset of pixels comprising the transition from the lens interior to the lens edge and a subset of pixels comprising the transition from the region exterior the lens to the lens edge.

10. The method of claim 9 wherein said comparison is performed among pixels from the subset of pixels comprising the transition from the lens interior to the lens edge.

11. The method of claim 9 wherein said comparison is performed among pixels from the subset of pixels comprising the transition from the region exterior the lens to the lens edge.

12. The method of claim 9 wherein said comparison is performed between pixels from the subset of pixels comprising the transition from the lens interior to the lens edge and the subset of pixels comprising the transition from the region exterior the lens to the lens edge.

13. The method of claim 4 wherein said relationship compared is a discontinuity in the pixels forming the lens edge.

14. The method of claim 4 wherein said relationship compared is a gradient deviation in the intensity of the pixels forming the lens edge.

15. The method of claim 4 wherein said relationship compared is a radial deviation in the location of the pixels forming the lens edge.

16. The method of claim 4 wherein said relationship compared is a spatial derivative in the location of the pixels forming the lens edge.

17. A method of inspecting an ophthalmic lens comprising:

capturing an image of the ophthalmic lens at least one electromagnetic frequency, said image consisting of pixels,

converting the image into a set of electrical values for each pixel,

choosing a starting pixel as the pixel-of-interest within the image,

A) determining if the pixel-of-interest has a feature characteristic,

B) for a pixel-of-interest having no feature characteristics;

1) changing the pixel-of-interest to another pixel along a path traversing the lens edge, and

2) repeating procedure A),

C) for a pixel-of-interest having feature characteristic;

3) comparing the electronic value of the pixel-of-interest to the electronic values of adjacent pixels,

4) changing the pixel-of-interest to the adjacent pixel with the best correlation to the feature characteristic,

5) repeating steps

     3) and

     4) until the pixel-of-interest represents completion of the feature, said feature being one of a radial deviation, a spatial derivative, a localized gradient deviation, a dip localized gradient deviation, a one-tail localized gradient deviation, and a discontinuity of the lens,

6) determining if the set of pixels gathered from procedure C) represents a lens edge,

D) for those sets of pixels that do not represent a lens edge, repeating procedure B), and

E) for those sets of pixels that represent a lens edge, comparing the relationship between the set of pixels to predetermined relationships to determine if the lens is acceptable.

18. The method of claim 17 wherein the electrical value comprises location and image intensity.

19. The method of claim 17 wherein the starting pixel is located proximate the center of the lens and the path traversing lens edge is along a ray extending from the center of the lens.

20. The method of claim 19 further comprising in procedure D) the step of comparing the set of pixels that do not represent a lens edge to a predetermined relationship to determine if the lens is acceptable.

21. The method of claim 18 wherein the feature characteristic is a change in image intensity.

22. The method of claim 19 wherein the approximate center of the lens is determined by taking at least one set of at least three points having an edge characteristic.

23. The method of claim 17 wherein the electrical value comprises location and image intensity gradient.

24. The method of claim 23 wherein the feature characteristic is an absolute value of an image intensity gradient.

25. An apparatus for the inspection an ophthalmic lens comprising:

a light source for illuminating a lens;

a camera placed to capture an image of the lens provided by the light source, the camera comprising a receptor wherein the image consists of a plurality of pixels;

means for converting the light striking the receptor at each pixel to an electrical value related to the intensity of light striking that pixel;

means for storing the electrical intensity value associated with each pixel in memory along with a value associated with the location on the receptor field;

a digital computer operably connected to the memory storing the electrical intensity values and location values, and capable of retrieving those values, the computer containing instructions for comparing intensity and location values among pixels to identify features of the lens comprised of sets of pixels, said features being at least three of the following features;

radial deviation and spatial derivative of the position values, localized gradient deviation, dip localized gradient deviation, and one-tail localized gradient deviation of the intensity values, and discontinuity of the lens, and the computer containing further instructions as to those features that render the lens unacceptable.

26. A method for automatically inspecting an ophthalmic lens, comprising the steps of:

collecting data to establish a plurality of edge triplet pixels in a number of groups, each of the number of groups defining a circle having a circle center;

obtaining an average circle center from the number of circle centers;

generating a processing annulus which contains the lens edge;

enhancing the lens edge to provide lens inner and outer transition edges;

tracking the inner and outer transition edges to extract the lens edge;

bridging discontinuities in the inner and outer transition edges that are below a predetermined number of pixels;

extracting at least three of features of the lens;

classifying as defects the extracted features that are different from corresponding thresholds.

27. The method of claim 26 further comprising declaring the lens defective when the defects are different from predetermined criteria.

28. The method of claim 26 further comprising the steps of:

assigning scores to each of the defective features in proportion to a severity of the defects of the extracted features;

grouping defective pixels associated with said defective features into defect groups based on an angular displacement among the defective pixels to determine if said defective pixels are part of a larger defect;

combining defect groups that meet a predetermined relationship to form larger defect groups;

weighing the scores of the defect groups according to impact on the quality of the lens;

adding the weighted scores to determine a total severity score; and

discarding the lens if the total severity score exceeds a predetermined number.

29. The method of claim 26, the extracting step extracts at least three lens features, said lens features including:

radial deviation from the inner and outer transition edges;

localized gradient deviation of an intensity value of a pixel with respect to pixels adjacent thereto;

spatial derivative that allows detection of a change in radius verses a change in angular displacement that is sharper than a change indicated by the radial deviation;

discontinuity that is not correctable by the bridging step;

dip localized gradient deviation that is sensitive to a gradient deviation of a pixel that is less than gradient deviations of neighboring pixels to allow identification of edge defects that are smaller that edge defects detected by the localized gradient deviation; and

one-tail localized gradient deviation that determines both negative and positive gradient deviations on one side of a pixel.

30. The method of claim 26, wherein the enhancing step performs the edge enhancement using pixels contained in the processing annulus.

31. The method of claim 26, prior to the collecting step, further comprising correcting a digital image of a container for holding the lens for known defective pixels in an imaging device.

32. The method of claim 31, wherein the correcting step includes interpolating between adjacent pixels of a uniform target image.

33. The method of claim 26, prior to the collecting step, further comprising locating the lens in a digital image by identifying an edge of the lens.

34. The method of claim 33, wherein the locating step performs a pixel to pixel search along a radial direction from an inner portion of the lens toward the edge.

35. The method of claim 33, wherein the locating step includes the steps of:

determining that an object is encountered upon detection of a pixel having a different intensity than an adjoining pixel;

tracking a contour of the object; and

determining that the edge is encountered if a curvature of the contour matched an expected curvature of the lens edge.

36. The method of claim 35, wherein the edge encounter determining step determines a count of pixels that form the contour and compares the count with a predetermined count.

37. The method of claim 33, after the locating step, further comprising determining whether the lens is absent from the container.

38. The method of claim 26, after the obtaining step, further comprising discarding a circle center with a greatest distance from the average circle center.

39. The method of claim 26, after the enhancing step, further comprising the steps of performing a skeletonization operation to reduce a width of the inner and outer transition edges to a single pixel;

and applying a thresholding operator to eliminate pixels not needed in the extracting step.

40. The method of claim 26, wherein the tracking step begins by searching from an inner boundary of the processing annulus outward.

41. The method of claim 26, wherein the bridging step bridges by extrapolation when the discontinuities are less than a predetermined size, and bridges by jumping when the discontinuities are greater than the predetermined size.

42. The method of claim 41, further comprising identifying as a defective feature the discontinuities that are bridged by jumping.

43. The method of claim 26, after the bridging step, further comprising transforming positional data from rectangular coordinates to polar coordinates.

44. The method of claim 26, wherein the classifying step includes comparing each of the extracted features to the corresponding thresholds.