System and method for color calibrating an image

• US 9,756,324 B1
• Filed: 04/10/2017
• Issued: 09/05/2017
• Est. Priority Date: 04/10/2017
• Status: Expired due to Fees

• Current Assignee: Gelt Inc.
• Original Assignee: Gelt Inc.
• Inventors: Flanagan, Mark S., Paolino, James
• Primary Examiner(s): Sherali, Ishrat I
• Application Number:
  US15/483,707
• Time in Patent Office: 148 Days
• Field of Search: 382162, 382294
• CPC Class Codes: G01J 3/463 Colour matching
• CPC Class Codes: G01J 3/52 using colour charts
• CPC Class Codes: G01N 21/78 producing a change of colour
• CPC Class Codes: G01N 21/8483 Investigating reagent band test-element handling not specific to a test method G01N33/4875; analytical elements specific to chemical analysis of biological material G01N33/52; autometer with reagent band G01N35/04
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 10/225 based on a marking or identifier characterising the area
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 20/695 Preprocessing, e.g. image segmentation
• CPC Class Codes: G06V 30/224 of printed characters having additional code marks or containing code marks
• CPC Class Codes: H04N 1/603 controlled by characteristics of the picture signal generator or the picture reproducer
• CPC Class Codes: H04N 1/6047 wherein the test pattern is part of an arbitrary user image
• CPC Class Codes: H04N 1/6052 Matching two or more picture signal generators or two or more picture reproducers
• CPC Class Codes: H04N 1/6055 using test pattern analysis
• CPC Class Codes: H04N 17/02 for colour television signals
• CPC Class Codes: H04N 23/45 for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
• CPC Class Codes: H04N 23/84 for processing colour signals
• CPC Class Codes: H04N 23/88 for colour balance, e.g. white-balance circuits or colour temperature control
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• CPC Class Codes: H04N 9/73 : Colour balance circuits, e.g. white balance circuits or colour temperature control camera processing pipelines for colour balance H04N23/88

Abstract

Systems and methods for color calibrating an image are described herein. In some embodiments, a method includes disposing a unique identifier and a fiducial marker that includes a plurality of color regions on an object. A first image of the object is captured with a first camera and a second image of the object that is captured with a second camera is received. The second image is associated with the first image based on the unique identifier and spectral information of at least a portion of the fiducial marker in the second image is compared with spectral information of at least the portion of the fiducial marker in the first image. Based on the comparison, the second image is resampled to substantially match at least the portion of the fiducial marker in the second image to at least the portion of the fiducial marker in the first image.

Claims

1. A method comprising:

disposing a unique identifier on an object;

disposing a fiducial marker on the object, the fiducial marker including a plurality of color regions;

capturing a first image of the object with a first camera;

receiving a second image of the object, the second image captured with a second camera;

associating the second image with the first image based on the unique identifier;

comparing spectral information of at least a portion of the fiducial marker in the second image with spectral information of at least the portion of the fiducial marker in the first image; and

resampling the second image to match at least the portion of the fiducial marker in the second image to at least the portion of the fiducial marker in the first image based on the comparison.

2. The method of claim 1, further comprising:

storing the first image in a cloud based server system; and

referencing the first image in the cloud based server system with the unique identifier.

3. The method of claim 1, wherein disposing the fiducial marker includes printing the plurality of color regions on the object.

4. The method of claim 1, further comprising:

correcting the second image for any physical distortion; and

quantifying and correlating the second image with respect to the first image.

5. The method of claim 4, wherein correcting the second image includes applying via a cloud based server system, linear transformation of position vectors on the second image.

6. The method of claim 4, wherein linearizing the plurality of color regions includes applying via a cloud based server system, linear transformation on at least the plurality of color regions of the second image.

7. The method of claim 1, wherein the object is a diagnostic assay.

8. The method of claim 7, further comprising:

analyzing the second image to collect quantifiable data from the second image, the quantifiable data relating to a test associated with the diagnostic assay.

9. The method of claim 1, wherein the fiducial marker is an adhesive label including the plurality of color regions.

10. The method of claim 1, wherein the unique identifier is at least one of a barcode, a hologram, and magnetic ink characters.

11. The method of claim 1, wherein the first image is captured under controlled conditions.

12. The method of claim 1, wherein spectral information includes at least one of intensity, wavelength, spectral value, Doppler shift, and Zeeman splitting.

13. The method of claim 1, wherein resampling the second image includes at least one of color correction, white balancing, gray balancing, gamma correction, and affine image transformation.

14. A method for collecting reliable data relating to a test from a second image, the method comprising:

disposing a unique identifier on a diagnostic assay;

disposing a spectral fiducial on the diagnostic assay, the spectral fiducial including a plurality of color regions;

capturing a first image of the diagnostic assay with a first camera;

at a processor;

receiving the second image of the diagnostic assay, the second image captured with a second camera;

associating the second image with the first image based on the unique identifier;

comparing spectral information of at least a portion of the spectral fiducial in the second image with spectral information of at least the portion of the spectral fiducial in the first image;

resampling the second image to match at least the portion of the spectral fiducial in the second image to at least the portion of the spectral fiducial in the first image based on the comparison; and

correlating spectral information of at least a portion of the resampled second image to corresponding information relating to the test to collect reliable data,

wherein the test is associated with the diagnostic assay.

15. The method of claim 14, wherein the diagnostic assay is a lateral flow immunochromatographic assay.

16. The method of claim 14, wherein the spectral fiducial is an adhesive label including the plurality of color regions.

17. The method of claim 15, wherein the lateral flow immunochromatographic assay includes a control area and a test area.

18. The method of claim 17, wherein the at least a portion of the resampled second image is the test area in the resampled second image.

19. The method of claim 15, wherein the lateral flow immunochromatographic assay is a medical diagnostic assay used for at least one of home testing, point of care testing, and laboratory testing.

20. The method of claim 14, wherein spectral information includes at least one of intensity, wavelength, spectral value, Doppler shift, and Zeeman splitting.

21. The method of claim 14, wherein resampling the second image includes at least one of color correction, white balancing, gray balancing, gamma correction, and affine image transformation.

22. The method of claim 14, further comprising:

correcting the second image for any physical distortion; and

quantifying and correlating the second image with respect to the first image.

23. The method of claim 22, wherein correcting the second image includes applying via the processor, linear transformation of position vectors on the second image.

24. The method of claim 22, wherein linearizing the plurality of color regions includes applying via the processor, linear transformation on at least the plurality of color regions of the second image.

25. The method of claim 14, wherein correlating includes applying a curve fitting formula on spectral information of the at least a portion of the resampled second image.

26. The method of claim 14, wherein the unique identifier is at least one of a barcode, a hologram, and magnetic ink characters.

27. The method of claim 14, wherein the first image is captured under controlled conditions.

28. The method of claim 14, further comprising:

storing the first image in a cloud based server database.

29. The method of claim 14, wherein the reliable data includes specification, label, and quantity of an analyte.

30. The method of claim 14, wherein the processor is a cloud based server processor.