Optical coin discrimination systems and methods for use with consumer-operated kiosks and the like

• US 9,036,890 B2
• Filed: 06/05/2012
• Issued: 05/19/2015
• Est. Priority Date: 06/05/2012
• Status: Active Grant

• Current Assignee: Coinstar Asset Holdings, LLC
• Original Assignee: Outerwall Inc.
• Inventors: Borg, Jeffrey A., Martin, Douglas A., Harrington, Timothy P.
• Primary Examiner(s): Drennan, Barry
• Assistant Examiner(s): Harandi, Siamak
• Application Number:
  US13/489,043
• Publication Number:
  US 20130322730A1
• Time in Patent Office: 1,078 Days
• Field of Search: None
• US Class Current: 382/136
• CPC Class Codes: G06F 18/2323 based on graph theory, e.g. minimum spanning trees [MST] or graph cuts
• CPC Class Codes: G06V 10/431 Frequency domain transformation; Autocorrelation
• CPC Class Codes: G06V 20/66 Trinkets, e.g. shirt buttons or jewellery items recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/80 Recognising image objects characterised by unique random patterns
• CPC Class Codes: G07D 5/02 Testing the dimensions, e.g. thickness, diameter; Testing the deformation

Abstract

Systems and associated methods for optical coin discrimination are disclosed herein. In one embodiment, a method for discriminating coins includes obtaining a digital image of a coin, identifying the outline of the coin using a suitable algorithm, and determining the diameter of the coin using the outline of the coin. The method of this embodiment further includes generating a rectangular image of the coin using, for example, a log-polar transform, generating a series of, for example, Fourier transforms from the rectangular image, and identifying spectral peak locations and intensities in the Fourier transform results. The diameter of the coin, spectral peak location, spectral peak intensity of the coin and/or other aspects of the coin can then be compared to known values for different coins to discriminate the coin.

Claims

1. A method for identifying coins, the method comprising:

obtaining a first image of a coin;

generating a second image from the first image;

transforming the second image to a 2D third image using a 2D Fourier transform;

identifying at least one of a location and an intensity of a spectral peak in the 2D third image; and

comparing at least one of the location and the intensity of the spectral peak in the 2D third image to at least one known coin property.

2. The method of claim 1 wherein the first image is a digital image.

3. The method of claim 2, further comprising:

converting the first image of the coin to a gray scale image.

4. The method of claim 1 wherein the first image is obtained in response to a signal generated by a coin movement.

5. The method of claim 1 wherein the first image is obtained by a digital camera running at a frame rate.

6. The method of claim 1 wherein generating the second image from the first image includes applying a log-polar mapping to the first image.

7. The method of claim 1 wherein generating the second image from the first image includes applying a polar mapping to the first image.

8. The method of claim 1, further comprising:

comparing at least one aspect of the first image to at least one known coin property.

9. The method of claim 8 wherein the at least one aspect of the first image is a coin diameter.

10. The method of claim 1, further comprising:

identifying an outline of the coin.

11. The method of claim 10 wherein identifying the outline of the coin includes applying a Canny edge detection method to the first image.

12. The method of claim 10 wherein identifying the outline of the coin includes applying at least one of Hough, Marr-Hildreth, Deriche, and Phase Congruency edge detection method to the first image.

13. The method of claim 10, further comprising:

determining a diameter of the coin from the outline of the coin.

14. The method of claim 9, further comprising:

setting first image pixel values to zero outside the outline of the coin.

15. The method of claim 10, further comprising:

applying a Gaussian filter to the first image.

16. A method for discriminating coins, the method comprising:

obtaining a first image of a coin;

identifying an outline of the coin from the first image;

generating a rectangular image from the first image by a log-polar mapping;

performing a Fourier transform of the rectangular image to generate a 2D transformed image; and

discriminating the coin by—

identifying at least one of a location and an intensity of a spectral peak in the 2D transformed image, and

comparing at least one of the location and the intensity of the spectral peak in the 2D transformed image to at least one known coin property.

17. The method of claim 16 wherein the first image is obtained in response to a signal generated by a coin movement.

18. The method of claim 16 wherein the first image is obtained by a digital camera running at a frame rate.

19. The method of claim 16 wherein the at least one aspect of the first image is a diameter of the coin.

20. A consumer operated coin counting apparatus comprising:

a coin input region configured to receive a plurality of coins;

a digital camera configured to capture first images of individual coins;

means for generating second images of the coins from the first images of the coins;

means for generating 2D third images from the second images of the coins using a 2D Fourier transform; and

means for discriminating the coins by—

identifying at least one of a location and an intensity of a spectral peak in the 2D third images, and

comparing at least one of the location and the intensity of the spectral peak in the 2D third images to at least one known coin property.

21. The apparatus of claim 20, further comprising means for comparing at least one aspect of the first images to at least one known coin property.

22. The apparatus of claim 20 wherein the means for generating the second images include means for log-polar mapping.

23. The apparatus of claim 20 wherein the means for generating the second images include means for polar mapping.

24. The apparatus of claim 20, further comprising means for detecting outline of the coins.

25. The apparatus of claim 20 wherein the at least one aspect of the first images is diameter of the coins.

26. A non-transitory computer-readable medium whose contents cause a computer to discriminate coins, the coins being discriminated by a method comprising:

receiving multiple coins;

capturing a first image of a coin;

generating a second image from the first image;

generating a 2D third image from the second image using a 2D Fourier transform; and

discriminating the coins by—

identifying at least one of a location and an intensity of a spectral peak in the 2D third images, and

comparing at least one of the location and the intensity of the spectral peak in the 2D third image to a known coin property.

27. The computer readable medium of claim 26 wherein the method further comprises accepting or rejecting the coin based on results of discriminating.

28. The computer readable medium of claim 26 wherein generating the second image from the first image includes a log-polar mapping.

29. The computer readable medium of claim 26 wherein the at least one aspect is a coin diameter.

30. A method performed by a computer having a computer code for identifying coins, the method comprising:

obtaining a first image of a coin;

generating a second image from the first image;

transforming the second image to a 2D third image using at least one of a Z-transform or a wavelet transform;

identifying at least one of a location and an intensity of a spectral peak in the 2D third image; and

comparing at least one of the location and the intensity of the spectral peak in the 2D third image to at least one known coin property.

31. A consumer operated coin counting apparatus comprising:

a coin input region configured to receive a plurality of coins;

a camera configured to capture first images of individual coins; and

a computer having a non-transitory computer-readable medium whose contents cause the computer to discriminate the coins by—

generating second images of the coins from the first images of the coins,

generating 2D third images from the second images of the coins using at least one of a Z-transform or a wavelet transform,

identifying at least one of a location and an intensity of a spectral peak in the 2D third images, and

comparing at least one of the location and the intensity of the spectral peak in the 2D third images to at least one known coin property to discriminate the coins.